EVALUATING THE IMPORTANCE OF SOIL MOISTURE … · 1.1 importance of agriculture in the southern...

EVALUATING THE IMPORTANCE OF SOIL MOISTURE AVAILABILITY (AS A LAND QUALITY) ON SELECTED RAINFED CROPS IN SEROWE AREA,

BOTSWANA

Esther Mweso March 2003

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Evaluating the importance of soil moisture availability (as a

land quality) on selected rainfed crops in Serowe area, Botswana

By

Esther Mweso Thesis submitted to the international Institute for Geo-information Science and Earth Observation in partial fulfilment of the requirements for the degree of Master of Science in Geo-information Science and Earth Observation, Soil Information Systems for Sustainable Land Management Degree Assessment Board Assoc. Prof. Dr. D.G. Rossiter (ITC) (Chairman/Second supervisor) Drs. S. de Bruin (University of Wageningen) (External Examiner) Dr. A. Farshad (ITC) (First supervisor) Dr. M. Lubczynski (ITC) (Internal Examiner)

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Disclaimer This document describes work undertaken as part of a programme of study at the International Institute for Geo-information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute.

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Abstract

The main objective of this research was to evaluate land with emphasis on soil moisture availability for rainfed maize and sorghum in Serowe area in Botswana.

To accomplish this, hydraulic properties such as actual soil moisture content, infiltration rate and hydraulic conductivity measurements were measured and examined verses soil properties in space. Interviews with farmers and agricultural extension staff helped to formulate land utilisation types (LUTs), land use requirements (LURs) and land characteristics (LCs). PS2 water limited production potential was used to evaluate the effect of soil moisture on yield of the selected crops, namely maize and sorghum. Automated Land Evaluation System (ALES) was employed to classify land into suitability classes, considering also the management.

The PS2 water limited potential revealed that increase in initial matric suction (PSIinti.) leads to yield reduction of 53% for maize and 57% for sorghum implying that reduction in soil moisture leads to decline in yield. The difference in yield at different levels of PSIint was significant (99%). There is positive relationship between moisture availability and yield of the crops. Late planting leads to low yield.

The negative relationship between actual soil moisture and infiltration rate as well as hydraulic conductivity on landscape basis does not give any meaningful results but the positive relationship on the basis of soil type, clearly declare the importance of soil and its variability.

The area has different soil types, which are spatially variable. The main soil types are Ferralic Arenosols (mainly in plateau), Calcic Luvisols, Pellic Vertisols, Eutric Nitosols (mainly in peneplain) and Endoleptic Regosols (mainly in hilland). The spatial variability of soil types influences soil moisture distribution.

Distribution of farmlands is mainly on clay loam and sandy clay loam soils which are found on the middle and lower terraces.

Evaluation results show that different map units have different suitability classes, and that soils of the hilland and plateau are not suitable for the land utilisation types currently practised in the area.

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Acknowledgements My deepest and profound gratitude go to Dr A Farshad, my main supervisor for his guidance, expert advices, encouragement and valuable comments. I am indebted for his assistance during fieldwork. I am grateful to Dr D.G Rossiter, my second supervisor for his advice, comments and willingness to assist even during his vacations. Bart Krol and Dr. Shrestha for their suggestions and advice during proposal writing. To the Government of Malawi, The Director of Land Resources Department, Mr J.N Mlenga, for giving me an opportunity to pursue this course, and The Deputy Director for Training, Mr J.J. Mussa for all the logistics made. Dr W. Siderius for his insights about the study area. I am sincerely grateful to my colleagues Ermias Betemariam, Enver Mapanda and Dennis Tembo with whom pleasant and hard times were shared, my colleagues from Soil Science Division, to my M.Sc. colleagues Ki Hwan Cho, Haig Sawasawa, Micheal Mwangangi, Amos Situma, Phoebe Luwum for their invaluable help in enhancing my computer skills. The people at Setekwane camp in Serowe, Botswana for good company-you really made our stay comfortable. I am especially grateful to my husband Sanless, and my children Chimango and Zenani for enduring my eighteen months absence and incessantly offering encouragement throughout the period. To my brothers, sisters, nephews and nieces for their prayers and moral support. To the Almighty God for seeing me through the programme

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Table Of Contents

Disclaimer .................................................................................... II

Abstract .......................................................................................III

Acknowledgements..................................................................IV

Table Of Contents .....................................................................VI

List of tables..................................................................................IX

List of figures................................................................................. X

List of Plates .................................................................................XI

Chapter 1: Introduction ............................................................. 1

1.1 IMPORTANCE OF AGRICULTURE IN THE SOUTHERN AFRICA DEVELOPMENT COMMUNITY (SADC) REGION ........................................................................................ 1 1.2 PROBLEM FORMULATION ........................................................................................... 2 1.3 RESEARCH OBJECTIVES .............................................................................................. 2

1.3.3 Overall objective ................................................................................................ 2 1.3.2 Specific objectives .............................................................................................. 3 1.3.3 Research questions............................................................................................. 3 1.3.4 Hypotheses ......................................................................................................... 3

1.4 CONCEPTUAL FRAMEWORK........................................................................................ 3 1.5 THESIS OVERVIEW...................................................................................................... 6

Chapter 2: A Literature review on soil water ...................... 7

2.1 SOIL MOISTURE ..................................................................................................... 7 2.1.1 Definition and importance ................................................................................. 7 2.1.2 Some concepts of soil moisture.......................................................................... 7 2.1.3 Soil water relations............................................................................................ 8 2.1.4 Infiltration .......................................................................................................... 8 2.1.5 Hydraulic conductivity....................................................................................... 9

2.2 MODELLING SOIL WATER ......................................................................................... 10 2.2.1 WOFOST.......................................................................................................... 10 2.2.2 PS123 ............................................................................................................... 10 2.2.3 Hydrus.............................................................................................................. 11 2.2.4 Water balance .................................................................................................. 11 2.2.5 Loss of water by plants .................................................................................... 12 2.2.6 Optimum availability of soil moisture.............................................................. 12

2.4 SOIL VARIABILITY .................................................................................................... 13 2.5 LAND EVALUATION .................................................................................................. 13

Chapter 3 Study area ............................................................... 17

VII

3.1 LOCATION ................................................................................................................ 17 3.2 CLIMATE .................................................................................................................. 17

3.2.1 Rainfall............................................................................................................. 18 3.2.2 Temperature..................................................................................................... 18 3.2.3Relative Humidity.............................................................................................. 19 3.2.4 Evapotranspiration .......................................................................................... 19 3.2.5 Wind ................................................................................................................. 20 3.2.6 Sunshine ........................................................................................................... 20

3.3 GEOLOGY................................................................................................................. 20 3.4 GEOMORPHOLOGY ................................................................................................... 21 3.5 VEGETATION............................................................................................................ 23 3.6 HYDROLOGY ............................................................................................................ 24

Chapter 4 Materials and Methods ........................................ 26

4.1 MATERIALS.............................................................................................................. 27 4.2 RESEARCH METHODS AND TECHNIQUES ................................................................... 27

4.2.1 Data exploration and Aerial photo interpretation........................................... 27 4.2.2. Soil survey...................................................................................................... 27 (A) Pit description..................................................................................................... 27 (B) Infiltration........................................................................................................... 28 (C) Hydraulic conductivity ....................................................................................... 28 (D) Soil moisture measurements............................................................................... 29 (E) Particle size distribution..................................................................................... 29 4.2.4 Land evaluation ............................................................................................... 30 (A) Interviews............................................................................................................ 30 (B) Climatic data access ........................................................................................... 30 (C) Production potential PS-2 .................................................................................. 31 (D) Selection of Land use requirements (LURs)....................................................... 33 (F) Building model in Automated Land Evaluation System (ALES) for Land Suitability Evaluation................................................................................................ 34

4.3 DATA PROCESSING AND ANALYSIS ........................................................................... 35 4.3.1 Statistical analyses........................................................................................... 35 (A) Hydraulic properties........................................................................................... 35 (B) PS-2 Production Potential water –limited production ....................................... 36 4.3.2 Geostatistical analysis ..................................................................................... 36 4.3.3 Remote Sensing ................................................................................................ 36

4.4 LIMITATIONS............................................................................................................ 36

Chapter 5 Soils ............................................................................. 37

5.1 SOIL AND SOIL FORMATION ...................................................................................... 37 5.1.1 Climate............................................................................................................. 37 5.1.2 Erosion............................................................................................................. 37 5.1.3 Vegetation ........................................................................................................ 39 5.1.4 Parent material ................................................................................................ 39

5.2 GENERAL DESCRIPTION OF LANDFORMS AND SOILS ................................................. 39 5.3 SOILS OF THE STUDY AREA....................................................................................... 44

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Chapter 6 Land use .................................................................. 48

6.1 LAND USE DEFINITON AND KINDS OF LAND USE ....................................................... 48 6.2 LAND UTILISATION TYPES IN THE SEROWE AREA ..................................................... 49

Description of land utilisation types (LUTs) ............................................................ 50 LUT1 Maize-based.................................................................................................... 50 LUT2 Sorghum-based ............................................................................................... 51

Chapter 7 Results and Discussion ...................................... 54

7.1 HYDRAULIC PROPERTIES.......................................................................................... 54 7.1.1 Infiltration rates ............................................................................................... 54 7.1.2 Actual moisture content ................................................................................... 57 7.1.3 Hydraulic conductivity (k) ............................................................................... 59 7.1.4 Relationship of the hydraulic properties.......................................................... 62

7.2 SOIL MOISTURE MAP ................................................................................................ 70 7.3 SPATIAL VARIABILITY .............................................................................................. 71 7.3 WATER-LIMITED PRODUCTION POTENTIAL PS2 ....................................................... 75 7.4 PHYSICAL LAND EVALUATION................................................................................. 81 SUMMARY...................................................................................................................... 85

Chapter 8 Conclusion and recommendations........................... 86

References..................................................................................... 88

APPENDIX A: SOIL HYDRAULIC PROPERTIES RESULTS ................................................... 91 APPENDIX B: SOIL PROFILE DESCRIPTION ...................................................................... 93 APPENDIX C: CLIMATIC FILE ....................................................................................... 108 APPENDIX D (A): GENERIC DATA VALUES FOR MAIZE AND SORGHUM ......................... 113 APPENDIX D(B): GENERIC DATA VALUES .................................................................... 113 APPENDIX E: GROWTH CYCLE FOR MAIZE AND SORGHUM ........................................... 114 APPENDIX F: GLOSSARY .............................................................................................. 114 APPENDIX G: QUESTIONNAIRE .................................................................................... 115 APPENDIX H: RESULTS OF PARTICLE SIZE DISTRIBUTION ANALYSIS ............................ 121 APPENDIX I: DECISION TREES ...................................................................................... 122

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List of tables Table 4- 1 The crop indicative values............................................................................ 32 Table 4- 2 LURs for maize ............................................................................................. 33 Table 4- 3 LURs for sorghum ........................................................................................ 34 Table 6- 1 Crop calendar................................................................................................ 49 Table 6- 2 Yield gap for LUT1 in 1999/2000 ................................................................ 51 Table 6- 3 Yield gap for LUT2 in 1999/2000 growing season ..................................... 51 Table 6- 4 Yield gap for late planting for LUT1 .......................................................... 52 Table 6- 5 Yield gap for late planting for LUT2 .......................................................... 52 Table 7- 1 Descritpive statistics for infiltration between landscapes ......................... 55 Table 7- 2 ANOVA for infiltration between landscapes.............................................. 55 Table 7- 3 ANOVA for infiltration between soil types ................................................ 56 Table 7- 4 Differences between pairs of means of soil types ....................................... 56 Table 7- 5 ANOVA for moisture content between the landscapes ............................. 57 Table 7- 6 Descriptive statistics for moisture between landscapes............................. 57 Table 7- 7 ANOVA for differences between pairs of soil types .................................. 58 Table 7- 8 Means and standard deviations of the soil types........................................ 58 Table 7- 9 The confidence intervals of the soil types ................................................... 59 Table 7- 10 ANOVA for hydraulic conductivity based on landscapes...................... 60 Table 7- 11 Descriptive statistics for saturated hydraulic conductivity..................... 60 Table 7- 12 Means and standard deviations of soil types ............................................ 61 Table 7- 13 The ANOVA for the means of saturated hydraulic conductivity........... 61 Table 7- 14 Differences in the means of saturated hydraulic conductivity of different

soil types. .................................................................................................................. 62 Table 7- 15 Correlation of hydraulic properties across the area................................ 62 Table 7- 16 Correlation of hydraulic properties by landscape ................................... 64 Table 7- 17 Correlation of hydraulic properties for soil types ................................... 67 Table 7- 18 The water limited yield of LUT1 for cropping year 1999/2000 .............. 75 Table 7- 19 water limited yield of LUT2 in the cropping year 1999/2000 ................. 75 Table 7- 20 LUT1 yield with different levels of PSIint ................................................ 76 Table 7- 21 ANOVA for water-limited yield of LUT1................................................. 76 Table 7- 22 ANOVA for water-limited yield of LUT2................................................. 77 Table 7- 23 The crop water functions at PSIint 500 and 2000cm for LUT1 ............. 77 Table 7- 24 The crop water functions at PSIint 500 and 2000cm for LUT2 ............. 78 Table 7- 25 Physical suitability for LUT1 and LUT2 .................................................. 83

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List of figures Fig 1- 1 A generalised flow chart of the conceptual frame work.................................. 5 Fig 2- 1 Some characteristic SMΨΨΨΨ-ΨΨΨΨ relations of soils of different texture ................ 9 Fig 2- 2Water fluxes that condition the volume of moisture in the rooting zone and

availability of water for uptake by roots............................................................... 12 Fig 3- 1 Location of Serowe the study area in Botswana............................................. 17 Fig 3- 2 The variation in rainfall distribution within years ........................................ 18 Fig 3- 3 Variations in rainfall amount between years ................................................. 18 Fig 3- 4 Temperature ranges of the study area. ........................................................... 19 Fig 3- 5 The relative humidity of the area. ................................................................... 19 Fig 3- 6 Sunshine hours over the year........................................................................... 20 Fig 3- 7 The Kalahari basin with the fault line running northwest to southeast ...... 21 Fig 3- 8 The geological map of Serowe.......................................................................... 21 Fig 3- 9 The stereogram depicting part of the study area. .......................................... 22 Fig 3- 10 The cross section of the study area ................................................................ 23 Fig 4- 1 Flow diagram of research activities................................................................. 26 Fig 4- 2 Theta probe........................................................................................................ 29 Fig 5- 1 Study area showing the sample blocks and pit profile points ....................... 41 Fig 5- 3 The geopedological map of Serowe.................................................................. 42 Fig 5- 4 The soil map of Serowe..................................................................................... 45 Fig 6- 1 Land use map of Serowe................................................................................... 48 Fig 7- 1Basic infiltration rates ....................................................................................... 54 Fig 7- 2 Saturated hydraulic conductivity at SVD 081................................................ 60 Fig 7- 3 Hydraulic properties across the area .............................................................. 63 Fig 7- 4 Relationship of hydraulic properties in hilland ............................................. 65 Fig 7- 5 Relationship of hydraulic properties in peneplain......................................... 66 Fig 7- 6 Relationship of hydraulic properties per soil type......................................... 68 Fig 7- 7 Soil moisture distribution map at 10cm depth ............................................... 71 Fig 7- 8 Soil moisture distribution map at 30cm depth ............................................... 71 Fig 7- 9 Moulded variogram parameters for AMC at 10 and 30 cm depths............. 72 Fig 7- 10 Soil moisture at 10cm depth (ordinary kriging ............................................ 73 Fig 7- 11 The error map at 10cm depth ........................................................................ 73 Fig 7- 12 Soil moisture map at 30cm depth (ordinary kriging) .................................. 74 Fig 7- 13 The error map for 30cm depth ...................................................................... 74 Fig 7- 14 Yield response to PSIint applied for LUT1 .................................................. 79 Fig 7- 15 Yield response to PSIint applied for LUT2 .................................................. 80 Fig 7- 16 Physical land suitability for LUT1 ................................................................ 84 Fig 7- 17 Physical land suitability for LUT2 ................................................................ 84

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List of Plates Plate 3- 1 Part of the study area, depicting plateau and hilland................................. 23 Plate 3- 2 One of the vegetation types in the study area.............................................. 25 Plate 3- 3 Gully erosion in some parts of the study area ............................................. 25 Plate 5- 1 A gully showing layers of depositional materials around Sokwe area in

Serowe ...................................................................................................................... 38 Plate 5- 2 Gully formation due to water erosion .......................................................... 38 Plate 5- 3 Ferralic Arenosols and Pellic Vertisols profiles .......................................... 42

EVALUATING THE IMPORTANCE OF SOIL MOISTURE AVAILABILITY (AS A LAND QUALITY) ON SELECTED RAINFED CROPS IN SEROWE AREA, BOTSWANA

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Chapter 1: Introduction 1.1 Importance of agriculture in the Southern Africa development Community (SADC) Region

Food security is a global concern as it affects the quality of life for both present and future

generations. But the environmental degradation poses a challenge to the scientific world since it

affects the agricultural production in terms of climatic changes and land degradation. This calls

for proper land use information at various levels of planning.

In many developing countries, agriculture, more especially crop production, is the major source

of livelihood. This is true in the Southern Africa Development Community (SADC) region.

Increasing the productivity of marginal rainfed agriculture is the key for many countries to

radically improve food security and reduce rural poverty.

As observed by Voortm (1985) increased agricultural production can be achieved by more

intensive use of land and by bringing additional land to cultivation both of which imply

substantial changes in land utilisation. Reliable predictions and recommendations can be made if

there is sound planning of changes in land use that requires a thorough knowledge of the natural

resources and reliable estimates of what they are capable of producing.

Despite the marginal ecological suitability, farmers in semi-arid areas depend on rainfed

agriculture. In countries of SADC alone, over two million people are estimated to live in areas

with average annual rainfall of around 500mm. The vast majority of these are at least partially

dependent on rainfed cropping for their subsistence (Gollifer, 1990) . Farmers in this zone face

high risk of crop failure due to variability of rainfall within and between years (Singh and Reddy,

1988; Tersteeg et al., 1992); In bad years, the harvest is very poor to suffice farmers demand.

Botswana is one of the countries in southern Africa that faces similar problems. Tersteeg et al,

(1993) further explain that in order to adapt to such an environment, farmers have typically

adopted strategies to spread and minimise risks like rearing livestock and small-scale commercial

activities. Parry et al, (1988) conclude that crop yields in these regions are very sensitive to the

amount of seasonal rainfall. Therefore, it is necessary to derive the relationship between average

yield decrease and relative evapotranspiration deficit as yield response factor in order to quantify

the effect of water stress (Landon, 1984). In agricultural production, climate is one of the factors


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that are considered critically. The most important parameters within climate are rainfall,

temperature and radiation (Sys et al., 1991).

Today, many developing countries like Botswana are trying to improve on agricultural production

with the aim of attaining food security.

1.2 Problem formulation

Drought is a major drawback in agricultural production and has become a worrisome situation in

the SADC region. Serowe area in Botswana, which is the study area for this research, experiences

long droughts. In some years farmers plant seeds without harvesting due to a number of factors,

such as poor rainfall distribution, use of late maturing crop varieties and poor choice of land for

agricultural production as more land is devoted to livestock production followed by settlement

(D. O. S. M, 2001). This calls for better planning of land for maximum productivity. Land

evaluation provides a set of data on potentials and constraints that can contribute to decisions on a

sustainable land use.

The suitability map (FAO, 1990c) available for rainfed agriculture in Botswana was conducted at

a national scale (Tersteeg et al., 1992) making the map generic. This map cannot give detailed

information of soils in a specific area but can be instrumental for further research. It is assumed

that there are some variations within an area for soil characteristics. This makes the suitability

map weak tool for planning because it can only evaluate production systems based on standard

level of inputs. Therefore, some studies are needed to focus on smallholder farmer level. Some

studies have been conducted in the area especially looking at the groundwater flow and recharge

for domestic use (SGC, 1988). These studies focussed on improvement of water supply to the

residents and livestock of the area. So far little has been done in Botswana on the role of soil

moisture availability in relation to crop yield. With no surface water resources, farmers rely on

rainfall for crop production yet this rainfall is not enough. Therefore there is need to establish the

water balance model for the area that can be used as a reference point for production of some

cereal crops. It is against this background that the study is going to evaluate land in Serowe area

in Botswana with emphasis on soil moisture availability.

1.3 Research objectives

1.3.3 Overall objective

The overall objective is to evaluate the effect of available soil moisture on yield of rainfed maize and sorghum in Serowe area in Botswana.


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1.3.2 Specific objectives

1. To determine the theoretical water-limited yield of grain crops (maize and sorghum)

2. To examine variations in distribution of different soil types

3. To analyse the relationship between soil types and hydraulic properties (actual

water content (AWC), hydraulic conductivity (k) and infiltration rate)

4. To evaluate soil moisture availability with respect to soil type and spatial variability

5. To describe principle land use types for rainfed smallholder grain products

6. To carry out land suitability evaluation with emphasis on soil moisture availability.

using PS123 and ALES softwares.

1.3.3 Research questions

1. What is the theoretical water limited yield for sorghum and maize?

2. Does the area have different soil- geomorphic units?

3. What are the different types of soil in the study area?

4. What are the factors that influence soil moisture availability?

5. Does spatial variability affect soil moisture distribution?

1.3.4 Hypotheses

1.Different soil types have different soil hydraulic properties.

2.Soil moisture distribution is controlled by spatial variability.

3.There is a spatial dependency between soil moisture and soil variability.

4.Soil properties can be used to infer the land quality moisture availability in the land

suitability evaluation process.

1.4 Conceptual framework

In carrying out a research, all activities and procedures have to be laid and followed properly in

order to succeed with that work. Similarly, there is a conceptual framework that was laid which

acted as a guide and provided links to different activities within the research life cycle. Referring

to the diagram (fig 1-1) of this conceptual framework a brief explanation is given.

The central point is the moisture availability, which is explained by different tools. The aim is to

find out the effect of soil moisture availability on the crop production (yield), for which maize


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and sorghum were selected. Each tool comes into play at different stage and one tool can be an

input to another tool. The major tools are PS2, which is a production potential programme for

estimating yield, and Automated Land Evaluation System (ALES), which is used to evaluate

land.

The entry point is the aerial photo and image interpretation leading to the establishment of map

units, which can be described after fieldwork, that is, when the soil contents of the units become

known. On top of the newly collected information, historical data are also used in different stages

of the study. Then soils are examined for their hydraulic properties.

Furthermore, interviews were conducted to the farmers and agriculture extension workers to get

data on agronomic, management, land use requirements and land characteristics. Apart from

getting data from interviews, LURs and LCs were developed based on environmental conditions

of the area. Climatic data was also accessed. These data were used to run PS2 (of PS123) and

ALES. The results of PS-2 programme and the LURs and LCs were put in ALES to build a model

to classify land into suitability classes. This final product can be used in land use planning.


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Fig 1- 1 A generalised flow chart of the conceptual frame work

Geomorphology Land cover units

Land qualities Interviews

LUR/LC

LUTs

API

Climatic data PS2

ALES

Topographic map Landsat

Geopedological units

Land suitability classes

Prefield work

Fieldwork

Post fieldwork


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1.5 Thesis overview

This research work is concerned with land evaluation with emphasis on soil moisture availability

as a land quality. The water limited production potential model is used to come up with

theoretical crop yield for the area. The model considers climatic conditions, crop attributes, soil

attributes and management practices in the study area.

Chapter 1 gives the introduction of research with its problem formulation, research objectives, research questions, hypotheses and conceptual framework. Chapter 2 is reviewing soil moisture and soil water related concepts, the empirical crop modelling

that simulates the ideal situation of the crop environment and land evaluation concepts which

deals with matters on what resources are available, the demands of the crop and how these match

to each other to come up with the suitability class.

Chapter 3 describes the study area in terms of location, that is, the geographical position of the

area, climate as it relates to the performance of the selected crops, geomorphology which gives

the picture on the terrain of an area, geology as it reveals the parent material of soils in the area,

vegetation and hydrology that is, all relevant environmental parameters.

Chapter 4 gives the research methods as well as the materials used in this research and problems

faced during the research work.

Chapter 5 discusses the soils in terms of factors that influence soil formation, description of

geomorphological units, soil profiles and description of soils occurring in the area.

Chapter 6 is on Land use/cover. This chapter covers land use and land cover in general, the land

utilisation types (LUTs) in the area, the LUTs being researched and their key attributes and the

differences in yield between actual and potential.

Chapter 7 presents the results and discussion on the sample sites, soil profiles, description of soil

map units, hydraulic properties and their relationship, soil moisture maps, the water limited

production potential and land evaluation.

Chapter 8 gives the conclusion and recommendations.


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Chapter 2: A Literature review on soil water

There is a relationship amongst soil, climatic factors and biotic factors. In this relationship, the

crop is the beneficiary. The soil water does interact with the above-mentioned factors.

2.1 Soil moisture

2.1.1 Definition and importance

Soil moisture is the water held in pores in the soil in liquid and vapour phases(Scott and Maitre,

1998). Soil moisture is the source of water for plant use in particular, in the rainfed agriculture.

There are a number of factors that affect the growth and performance of crops like soil, water and

evapotranspiration (ET). Water serves four general conditions in plants: the major constituent of

the physiologically active tissue; As a reagent in photosynthetic and hydrolytic processes; as a

solvent for salts, sugars and other solutes and water is essential for the maintenance of turgidity

necessary for cell enlargement and growth. Therefore, It is vital to check at which crop growth

stage is moisture critical so as to take mitigation measures like timely planting and soil and water

conservation practices (Kamoni, 1985). In the development of a crop, the annual mean figures as

well as their distribution during the year are important.

2.1.2 Some concepts of soil moisture

Available water capacity (AWC) is the amount of water that the soil can store; that is available

for use by plants expressed as volume fraction or percentage (USDA, 1997).

Field capacity (FC) is the maximum water content that the soil holds following free drainage. It

represents the condition of each individual soil after the large pores have drained freely under

gravity (Landon, 1984). This in practice is usually taken as the moisture content of a soil, which

has drained freely for two days after saturation.

Wilting point (WP) is the condition at which the plant loses turgor and is commonly estimated

by measuring the 15-bar percentage of a soil (wilting point).

Permanent wilting point (PWP) is defined as soil moisture content at which the leaves do not

recover their turgor if subsequently placed in a saturated atmosphere. PWP is taken as the lower

limit of available water so that water in drier soils is assumed to be not available to plants.

Water in unsaturated soils is held in thin films on soil particles or pore surface or as wedges

where the particle or pore surfaces lie sufficiently close together (Landon, 1984). In practice,


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water uptake by the roots is affected by the depth and density of rooting, gradients in water

potential and hydraulic conductivity of both soil and roots.

Under irrigation conditions, the relationship between crop yield and water supply can be

determined when the crop water requirements and crop water deficits on one hand and maximum

and actual crop yield on the other hand are quantified. Doorenbos and Kassam (1979) describe

that there is relationship between yield and evapotranspiration and that in general, the decrease in

yield is proportionally greater with increase in water deficit.

2.1.3 Soil water relations

In irrigated maize, cumulative pan evaporation ratio of 1.0 gives high yield as well as maximum

efficiency of water use as compared to ratios of 1.4, 1.2, 0.8 and 0.6 (Prasad et al., 1997). This

suggests that there is a threshold of moisture that the crop requires to perform economically other

factors remaining constant. Maximum available moisture can be defined as the amount of water

present at field capacity diminished by the amount, which is present at permanent wilting point.

Crop water use (also known as evapotranspiration (ET)) is influenced by prevailing weather

condition, available water in the soil, crop species and growth stages (Al-Kaisi and Broner, 1992).

After the rain or irrigation, actual ET is higher than when the soil or crop surface is dry. However,

not all the available water capacity can be considered as equally available to plants. It is this

readily available water held in at low tension within the larger soil pores, which is particularly

affected by soil structural conditions. In many cases crops must rely on water that is stored in the

soil (residual moisture) at the end of the rainy season (Landon, 1984). In crop production, there

are a number of factors needed like solar radiation nutrients and moisture but the availability of

soil moisture is the key to plant growth and to the net production of crops.

Tersteeg et al., (1993) cite (Pike 1971) that in Botswana, rainfall varies spatially from 250mm to

700mm that is erratically distributed between years. The soil moisture availability is also affected

by the farming system in the area.

2.1.4 Infiltration

Infiltration refers to the vertical intake of water into a soil usually at the soil surface. The larger

the pore size the greater the infiltration rate. The infiltration rate determines a soils water

adsorption capacity that reveals the likely behaviour of soil under precipitation. It is the rate of

this process, relative to the rate of water supply that determines how much water will enter the

unsaturated soil zone, and how much if any, will runoff (Hillel, 1982). The infiltration rate of a


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soil remains the same for a very long time unless the soil itself is changed. After infiltration,

percolation takes place which is a general term for downward flow of water in the unsaturated

zone (Dingman, 1993)

2.1.5 Hydraulic conductivity

The soil moisture availability is related to soil hydraulic properties. Hydraulic conductivity (k) is

the rate at which water moves through a porous medium under a unit potential gradient. It is also

called permeability (Dingman, 1993). Knowledge of the hydraulic properties is indispensable for

addressing many soil, hydrological, environmental, ecological and agricultural problems (USDA,

1997). These hydraulic properties are influenced by texture, structural characteristics and organic

matter content of the soil (Landon, 1984; Lascano, 1997; Ward and Robinson, 1989). In general

there is rapid decrease of K with decrease in water content in unsaturated soils due to rapid

draining of larger pores (Landon, 1984). Kosta (1994) further explains that soil water in

unsaturated zone is of special importance at the partitioning of water in form of precipitation.

There is a relationship between soil moisture retention curve and hydraulic conductivity (k).

Different methods are used to measure k and these should give similar results. Fig 2-1 below

shows some characteristic matric suction relations of soils of different textures.

Fig 2- 1 Some characteristic SMΨΨΨΨ-ΨΨΨΨ relations of soils of different texture Source: Landon (1984)


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2.2 Modelling soil water

There are several empirical models in soil water that are used to predict the yield of crops in various situations. Such empirical models are useful as they forewarn the future in terms of agricultural production.

2.2.1 WOFOST

This is an empirical modelling tool that explains crop growth on the basis of the underlying

processes such as photosynthesis and respiration, and how these processes are affected by

environmental conditions. The model describes crop growth as biomass accumulation in

combination with phonological development. It stimulates the crop life cycle from sowing to

maturity. The basis for calculation of dry matter production and yield is the rate of gross carbon

dioxide (CO2) assimilation by the green canopy, determined by the level of irradiance, the green

area of the crop capable of intercepting the incoming radiation, the photosynthetic characteristics

of the crop species and the prevailing temperature. A part of assimilates is used by crop for

respiratory processes to provide energy for its own maintenance. The remainder of assimilates is

available for the increase in structural dry matter. The increase in total weight is partitioned over

the roots, stem and storage organs (Wokabi, 1994).

2.2.2 PS123

This is a procedure that assumes the ideal situation of a crop. All factors that affect the growth

and performance of a crop are considered to run the model. The PS123 programme is a crop

growth simulation model. The basis for calculating the biophysical (crop) production potential

(yield) is the capability of green plants to reduce atmospheric CO2 to carbohydrates. As the intake

of atmospheric CO2 takes place through the stomata, which also forms the defence system of the

plant against moisture stress, there is a strong correlation between the rate of transpiration and the

rate of assimilation of CO2 (Driessen and Konijn, 1992). The PS-1 production situation represents

the least possible analytical complexity, as only solar radiation and temperature during the

growing period and the biophysical characteristics of the crops are taken into account. All other

land qualities are assumed to be optimum. The PS-2 simulates the water limited production

potential. Production possibilities are determined by irradiance of photosynthetically active

radiation temperature and availability of water (Driessen and Konijn, 1992). Crops have different

response to the total received radiation and how much can be converted to growth and yield.


11

2.2.3 Hydrus

This is a programme that simulates two-dimensional variably saturated water flow, heat

movement and transport of solutes involved in sequential first order decay reactions. The

programme numerically solves the Richard’s equation for saturated-unsaturated water flow and

convection dispersion type equations for heat and solute transport. The flow equation

incorporates a sink term to account for water uptake by plant roots. The programme may be used

to analyse water and solute movement in unsaturated, partially saturated or fully saturated porous

media (Simunek et al., 1999).

2.2.4 Water balance

Water transport and retention processes in the soil are complex. The soil surface is exposed

continuously to changing radiation fluxes, which create diurnal cycles of temperature, relative

humidity, and even water vapour fluxes caused by temperature gradients. Plants take up water

from the soil through their roots and lose it through transpiration. This water uptake is controlled

by soil matric suction in the rooting zone, which partly controls the rate of infiltration and

sorptivity, which is the combined influences of capillary action and adhesive forces to soil and

solid surfaces. The status of the plant influences the rate of carbon dioxide (CO2) supply because

the stomatal openings are affected by the water potential in the plant (Van Keulen and Wolf,

1986).

The crop water requirements vary considerably with the crop, crop development stages and their

length, and with the evaporative demand of the atmosphere. The water balance can be described

as follows:

RMS = [UPFLUX=(CR+D)-TR]/RD (2-1)(Van Keulen and Wolf, 1986)

Where,

RSM is the rate of change of volume fraction of moisture in the rooting zone (cm d -1)

UPFLUX is the net of water vapour flow through the upper boundary of the rooting zone (cm d-1)

(CR+D) is the net rate of water flow through the lower boundary of the rooting zone (cm d-1)

TR is the actual rate of transpiration (cm d-1)

RD is equivalent depth of the rooting zone (cm).


12

Fig 2- 2Water fluxes that condition the volume of moisture in the rooting zone and availability of water for uptake by roots

Source: Driessen and Konijn (1992)

2.2.5 Loss of water by plants

Uptake of water by crops is almost equal to the rate of transpiration. Plants can produce to their

biophysical potential only if the availability of water is optimum. Plants curb their consumption

of water if supply is constrained; actual transpiration becomes less than maximum and production

becomes less than the biophysical potential (Driessen and Konijn, 1992).

2.2.6 Optimum availability of soil moisture

Most of the times water stress in plants is associated with shortage of water in the soil. However,

shortage of air (oxygen) in the soil interferes with uptake of water by the plant. Some plants are

adapted to such conditions because of the development of some tissues (Aerenchyma) through

which oxygen diffuses easily from the tissues of the leaves into the shoot axis and roots(Larcher,

1980) . Plants that are not equipped with aerenchyma in their roots have difficulties in taking up

water in waterlogged environments; they show symptoms of drought and close their stomata.


13

There are two critical boundary values in the range of moisture in the soils. One is associated with

wetness and low matric suction and another one with drought and high suction.

2.4 Soil variability

Soils from different areas behave differently (spatial and temporal variability of soils) for

example in water holding capacity, infiltration rate, drainage and erosion risk. This implies that

different management practices are also applied for sustainable management. According to

Wilding and Drees (1983) spatial studies of soil properties and the nature of soil variability

depend largely on the scale of observation and properties in question. Despite the economic and

cultural importance of soil maintenance, detailed international surveys suggest that soils under

agricultural use are in danger of losing capacity to fulfil their economic, cultural and ecological

functions (Jazairy, 1993)

Soil characteristics vary in time and space (Parry et al., 1988). Models can be developed to

explain these variations. There are a number of models that are used depending on the purpose of

the project. Soil surveys are one type of the models that are carried out to obtain information

about the distribution of soil characteristics of an area. This can be detailed or semi-detailed soil

survey based on the geopedological approach (Zinck, 1988/89) that emphasises the strong

integration of geomorphology and pedology. It is based on hypothesis that boundaries drawn by

landscape analysis separate most of the variation in the soils and sample areas are representative

(Girma, 2001). This is not a complete approach as we assume that soils within the landscape can

have variations as well hence the application of geostatistical approach is employed to

supplement the information gaps in the variations of soils in time and space. The Continuous

Model of Spatial Variation (McBratney and Gruijter, 1992) can be used to assess the variations

of soil within the soil map unit that is homogeneous so as to come up with detailed information of

that soil map unit and interpolate to the unvisited points.

2.5 Land evaluation

Environmental attributes such as land and topography play controlling roles in the spatial

distribution of soil moisture content (Qiu et al., 2001). This necessitates the usefulness of land

evaluation in order to come up with a sound land use planning. Land evaluation can be defined as

the assessment of land performance when used for specified purposes (FAO, 1983). Land

evaluation predicts how each land area would behave if it were used according to each system. In


14

order for the evaluation to be meaningful it should take into account the economics of the

proposed alternative enterprises, the social and the environmental implications of such

enterprises. However, most land evaluation methods have been focussed on assessing the

potential of land without considering the economic part. Carrying out area specific land

evaluation can provide good guidance for planners at local level.

Automated Land Evaluation System (ALES)

Land evaluation mostly deals with demand side of the resources (land use requirements) and the

supply side (land qualities). The two are matched to come up with the land suitability class.

Automated Land Evaluation System (ALES) is a programme that is used by land evaluators to

build expert systems to evaluate land (Rossiter and Van Wambeke, 1993). It should be noted that

the system is an empty shell that requires knowledge from the expert.

The entities evaluated by ALES are map units which may be defined either broadly (as in

reconnaissance surveys and general feasibility studies) or narrowly (as in detailed surveys and

farm scale planning (Rossiter and Van Wambeke, 1997).

The system has also the format of an expert system based on the FAO framework for land

evaluation. It allows the user to build decision trees, containing ratings for land qualities and

requirements for land utilisation types. The four major components are:

• A knowledge base (the actual expert system), containing descriptions of different land

uses in both physical and economic terms

• A data base containing, information on the natural resources

• An inference algorithm, allowing matching of land and land uses

• An explanation facility, which permits the analysis of results

The knowledge base is specified by the user and contains the relations between land and land use

requirements, in which land use can either, be a single crop or a crop rotation. Land use

requirements are defined in the system in terms of levels of limitation. Similar levels of

limitations may originate from different combinations of land characteristics as derived from the

decision trees.

The database to be developed by the user contains information from natural resource surveys.

Both discrete and continuous information can be handled by the system, which provides

possibilities to generate missing information through decision tress.


15

In the inference algorithm, matching of land qualities and land use requirements takes place

according to user defined procedures, which results in an evaluation matrix, that allows easy

selection of the best land for a particular land use. Suitability is expressed quantitatively,

according to the framework principles, and in relation to a non-constrained yield or ‘nominative’

yield for use in economic evaluation.

The explanation facility allows the user to analyse the results through a backward chain in the

system. Interactive procedure is possible to improve the evaluation procedure.

ALES is able to evaluate land in physical terms only, or both physical and economic terms. Each

evaluation consists of land utilisation types like proposed land uses and a set of land mapping

units. In physical evaluation, map units are assigned physical suitability classes, which indicate

the relative suitability: s1, s2 s3/nl and n2. ALES can also compute an economic evaluation

following the computation of a physical evaluation. All components of economic model have to

be present otherwise evaluation will not be possible. One of the limitations of ALES is that it has

no input or output for maps.

It is important for evaluators to construct decision trees to infer each land quality from its set of

diagnostic characteristics. These are hierarchical multi-way keys, in which values of the

diagnostic land characteristics (LCs) are the diagnostic criteria and the result is the severity level

of the land quality to be evaluated (Rossiter, 2001b). This is where the expert knowledge of the

evaluator has to be put into systematic form.

Certain concepts and definitions are needed to form a basis of land evaluation. These concern the

land quality, land characteristics, diagnostic factors and land requirements. The following

definitions are from the FAO (1983):

Land quality (LQ) is an attribute of land that acts in a distinct manner in its influence on the

suitability of the land for a specific kind of use like temperature regimes, soil moisture

availability and drainage. It directs attention towards the way in which the land affects suitability

for use.

Land characteristic (LC) is an attribute of land that can be measured or estimated, and that can

be employed as a means of describing land qualities or distinguishing land units of differing

suitabilities for use.

Diagnostic factor is a variable that is used to estimate land qualities in land evaluation. In some

cases a land quality can be satisfactorily described on the basis of a single land characteristic or a

combination of a number of land characteristics.


16

Land use requirement (LUR) is the conditions of land necessary or desirable for the successful and sustained practice of a given land utilization type. It considers crop requirements, management requirements and conservation requirements. Land utilization type (LUT) is a specific manner of occupying and using the land, with

specified management methods in a defined technical and socio-economic setting. In the context

of rainfed agriculture, it can refer to a crop, crop combination or cropping system.

Land mapping units (LMU) as defined by Rossiter (2001b) is a specific area of that land that

can be delineated on a thematic map and whose land characteristics can be determined. These are

sets of maps delineations designated by a single name, and representing a single legend category.


17

Chapter 3 Study area

3.1 Location

The study area is a part of the Serowe area in Botswana located 300km northwest of Gaborone,

which is the capital (fig 3-1). The elevation of Serowe ranges from 1060 to 1240m above sea

level. The geographical position is within the range of 16o 07’37” to 26o 54’10” East and 22o

14’10” to 22o 30’33” South (UTM coordinates of 410000, 7650000 and 49000, 7510000)

covering an area of about 244048ha.

Fig 3- 1 Location of Serowe the study area in Botswana Reasons for selecting Serowe area:

1. Semi-arid area with rainfall range of 450-470mm/annum

2. Subsistence agriculture is predominant

3. High erosion potential due to topography and sealing

3.2 Climate

Serowe area in Botswana is characterized by semi-arid climate with cool dry winters and hot moist summers.


18

3.2.1 Rainfall

The mean annual rainfall is 477mm as reported by Swedish Geological Survey (1988). The

rainfall is highly variable in time and space with growing period starting from November to April

(Fig 3-2 and Fig 3-3). Botswana in general falls under ustic regimes based on the available

climatic data (De Wit and Nachtergaele, 1990). During the rainy season and indeed all the year

round , monthly totals are consistently exceeded by the potential evaporation for the same period.

Rainstorms are frequently intense and of short duration and localised. An entire month’s total can

fall within the space of a few hours over a small area (SGC, 1988).

Rainfall distribution within years

050

100150

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Time (months)

Rai

nfal

l (m

m)

Fig 3- 2 The variation in rainfall distribution within years

Rainfall variations between years

0

500

1000

1986 1988 1990 1992 1994 1996 1998 2000

Time (Years)

Rai

nfal

l (m

m)

Fig 3- 3 Variations in rainfall amount between years

3.2.2 Temperature

The temperature goes as high as 30 or more before rainy season in October whilst in winter

period (May to August) the area experiences low temperatures of minimum of 12 oC. This period


19

is also characterised by low wind speed and long hours of sunshine. The radiation and

evaporation are at their lowest levels. Fig 3-4 below shows the daily temperature for the year

2000.

Temperature

0.00

10.00

20.00

30.00

40.00

Jan Feb Mar Apri May Jun Jul Aug Sep Oct Nov Dec

Time (months)

Tem

pera

ture

Fig 3- 4 Temperature ranges of the study area.

3.2.3Relative Humidity

The area experiences low relative humidity during winter (May to August) with

minimum of 45% but start increasing in late August and reach a maximum of 70%. Refer

to fig 3-5

Relative Humidity

020406080


Months

Rel

ativ

e H

umid

ity

(%)

Fig 3- 5 The relative humidity of the area.

3.2.4 Evapotranspiration

As a semi-arid area, Serowe experiences high evapotranspiration rates in summer when

temperatures are high and moisture is available. Low evapotranspiration occurs during winter

when soils become drier. Soil moisture of <0.05cm3/cm3 were recorded to a depth of 1.80m near

the ADAS station in mid August (Timmermans and Meijerink, 1999) indicating very dry soils.

Evapotranspiration rates varying from 0.2 to 10mm/d have been estimated by different methods

during different previous studies carried out in the area.


20

3.2.5 Wind

Wind can be described as air in motion. It moves in circuits and is powered by unequal heating of

large masses of air. Wind plays an important role in rain formation. Since the earth is warmed

differently, the air above these surfaces absorbs different amounts of heat. Warm air rises while

cool air sinks which creates the environment for flowing air movement. This movement ends up

in the formation of clouds and eventually rain is formed. The average wind speed in the study

area is 1.22m/s.

Windspeed

0.00

0.50

1.00

1.50

2.00


Months

Win

dspe

ed

Figure 3-6 Wind speed graph

3.2.6 Sunshine

Sunshine is a form of measuring solar radiation. The World Meteorological Organisation defines

sunshine hours as the sum of the time intervals during which the direct solar irradiance exceeds a

threshold of 120Wm-2 . In crop production, this amount of solar irradiance plays a major role in

photosynthetic process. The area receives an average of 8.6 sunshine hours per day.

Sunshine hours

0.00

5.00

10.00

15.00

Jan

Feb MarApr

iMay Ju

n Jul

Aug Sep OctNov Dec

Months

Sun

shin

e

Fig 3- 6 Sunshine hours over the year

3.3 Geology

There is a fault line running from northwest to southeast that led to the formation of a bed-like

feature in the Kalahari (Fig 3-7). The sandveld (see 3.4) consists of sandstone of different nature


21

in terms of colour (red, yellowish and whitish). There are some intrusions of sand in the hardveld

(see section 3.4). Around Mogorosi area, there is occurrence of ironstone of the plinthic groups.

Some calcium carbonate concretions also appear in some parts of Mabeleapodi that is in the

northeast of the study area and around Sokwe hill. In the hardveld there are Andesite deposits that

were cooled under water. Fig 3-8 shows the geology of the study area.

Fig 3- 7 The Kalahari basin with the fault line running northwest to southeast

Fig 3- 8 The geological map of Serowe

3.4 Geomorphology

Following the geopedological approach (Zinck, 1988/89) three main physiographic units have

been distinguished, namely Sandveld, escarpment and hardveld. The escarpment stretching along


22

the plateau edge is not of the same breadth throughout the unit. From the escarpment going to the

east, there is a stretch of undulating to rolling land where there is existence of some rock

outcrops. In general, the escarpment outlines the eastern limit of the stormberg basalt despite the

fact that basalt also occurs extensively to the east of the escarpment line between Serowe and

Mogorosi village (Wellfield Consulting Services, 1998).It should be noted that it is difficult to

come up with geopedological terms for Sandveld and Hardveld, the terms which are used by the

local researchers. The sandveld matches the term plateau, and the hardveld is a peneplain, with a

few terrace levels which can be termed as glacis terraces resulted from peneplanation (Zinck,

1988/89).

This is also approved by occurrence of the inselbergs that are exposed in the area. In between the

plateau and the peneplain, there is a hilly area. Keeping that in mind, three landscapes were

adopted and identified namely Plateau, Hilland and Peneplain. The elevation ranges from 1000m

to 1250m from the hardveld to the sandveld Figure 3-9 shows the stereogram depicting the study

area; plate3-1 showing an overview of the area and figure 3-10 presents the cross section from

west to east.

Fig 3- 9 The stereogram depicting part of the study area.


23

Plate 3- 1 Part of the study area, depicting plateau and hilland

Cross section

1000

1050

1100

1150

1200

1250

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000

Distance (m)

Hei

ght (

m)

Pu111

Hi111

Hi112

Pe114

Pe111 Pe113

Fig 3- 10 The cross section of the study area

3.5 Vegetation

The sandveld is covered by variable dense of trees, shrub and grass (D. O. S. M, 2001). Denser

and taller vegetation is generally along the strip of the escarpment contrary to the shallowness of

the soils in this area. However, from field observations, it was noted that the escarpment soils

have high moisture retention capabilities. The common species are Terminalia sericea,

Dichrostachys cinerea, Ochna pulchra and Burkea Africana on sandveld whilst Accacia

mellifera, Ziziphus mucrotana, Accaci tortillas and Accacia luederitzii on the hardveld.


24

3.6 Hydrology

The area has seasonal rivers which means they flow for only part of the year. Sometimes they

may only flow for a few hours after heavy rains in summer (SGC, 1988). The drainage network is

more pronounced in the east of the escarpment. The rivers are deeply incised due to gully erosion

as observed around the Sokwe area (Plate3-3) whilst in the escarpment the river course mostly is

in the bedrock. The water table lies between 10 to 40m in the hardveld and 40 to 60m in the

sandveld (D. O. S. M, 2001).


25

Plate 3- 2 One of the vegetation types in the study area

Plate 3- 3 Gully erosion in some parts of the study area


26

Chapter 4 Materials and Methods

Fig 4- 1 Flow diagram of research activities

Climatic data Literature review Aerial photographs Landsat TM

Problem definition, research objectives, research questions

Develop questionnaire

Image interpretation

Geopedological units for sampling

Conduct interviews

Sampling: pits, mini pits, soil

Run PS2 programme LUTs,LQs,

LURs, LCs,

Statistical and geostatistical

Build computer model in ALES for land evaluation Laboratory analysis

Compute the evaluation

Land suitability classes

Presentation of results

Post fieldwork

Fieldwork

Pre-fieldwork


27

4.1 Materials

The existing aerial photographs at scale of 1:50000 Satellite images of Landsat TM (August 2000) and IKONOS covering 10*10km in the western part of Serowe. Existing soil maps of scales: 1:250000 (De Alwis, 1985) and 1:1000000 (FAO, 1990b)

Field documents (FAO, 1990c; Joshua, 1991; Nampad, 2000) ILWIS 3.1 software PS123 software ALES software Climatic data: Rainfall (1986-2000), Relative humidity, Wind speed, Evapotranspiration and

Temperature for some of the years.

4.2 Research methods and techniques

4.2.1 Data exploration and Aerial photo interpretation

The research work was divided into three phases namely pre-fieldwork, fieldwork and post-

fieldwork. The first stage was research proposal writing that comprised literature review and

collection of general information of the study area. Then preparation for filed work was followed.

Due to missing of some of the aerial photographs, it was not possible to produce a complete aerial

photo interpretation to develop a base map. Rather, a combination of the aerial photos and

information extracted from the Landsat image were used to come up with a temporary base map.

Three strata were produced, one on the sandveld, another one on the hardveld and the last one

cutting across sandveld and the hardveld on the north-eastern part of the study area. This was

corrected in the field and finally came up with two blocks (see fig 5-1).

4.2.2. Soil survey

A reconnaissance survey was carried on the first day to get an overview of the area. The main aim

was to get acquainted with the area, infrastructure and to figure out where to make pits for soil

profile description and also the position of the farmlands. The base map was corrected in the field

to suit the reality of the study area.

(A) Pit description

Full pit and mini-pits were studied on the main mapping units. Apart from soil description, other

tests like infiltration; hydraulic conductivity and moisture measurements were conducted. Pits


28

were dug to a depth of 120m and continue with auguring down to a depth of 180m. Auger hole

observations were made subjectively on some of the sample points. Soils were described

according to the 3rd edition (Revised) (FAO, 1990a).

(B) Infiltration

This was measured using double ring infiltrometer (Eijkelkamp, 1998). Only two sets were used

due to the lack of floaters. The test points were selected and prewetted the previous day. The

rings were pushed ten (10) cm into the soil followed by pouring water into the ring to a depth of

10cm. The drop in water surface (depth) was recorded at every minute until a base saturation was

reached (Plate 4-1). These tests were done on random points as well as on the pit description

sites. The whole procedure was taking about two hours for the sandy soils but longer in heavy

soils.

Plate 4- 1 Conducting infiltration test on one of the sites

(C) Hydraulic conductivity

The inverse auger hole method applied. The test was done after the infiltration test has taken

place. The site where rings were placed was augured to a depth of 100cm, with ten cm diameter

and water was poured into the auger hole. The drop in water depth was measured every 60

seconds for a period of ten minutes. It should be noted that for heavy soils (mainly vertisols) in

some instances, this test was a failure because of development of cracks in the shrinking soils

such that water poured in the auger hole was drained within few seconds.


29

(D) Soil moisture measurements

The soil moisture measurements was done in two different ways: (i) Gravimetric method: Samples were taken at two different depths of 0-10cm and 20-

30cm. The samples were weighed and placed in the oven at 105oC for 12hours. After oven

drying, the samples were reweighed to get actual moisture on date of sampling.

(ii) Volumetric method: Theta probe is an instrument used to measure volumetric soil

moisture θv, in the soil instantly (fig 4-2). Volumetric soil moisture content is the ratio

between the volume of water present and the total volume of the sample. This is expressed as

percentage (%vol), or a ratio (m3/m3) (Eijkelkamp, 1998). The probes were inserted into the

soil and a reading was taken after 8 seconds to give room for stabilisation of the instrument.

The theta probe was not reliable in the sense that at some sites (especially sandy soils) it

would give negative readings hence it was abandoned.

Fig 4- 2 Theta probe

(E) Particle size distribution

Soils from different soil horizons from a number of profiles and auger holes were brought to

I.T.C and laboratory analysis on particle size distribution was performed using pipette method.

The following is the procedure for pipette: 15ml of water and 15ml of H2O2 30% were added to

each 20g of soil samples. The samples were left on water bath at temperature of 80oC for

overnight. Then 300ml of water were added and boiled for one hour. After cooling, the samples

were centrifuged and 5mls of 1M CaCl2 solution was added. The samples were then placed on a

shaker for 16hours. Sand was separated with a 50µ sieve. The suspension of clay and silt were

transferred into 1000ml cylinder. The clay and silt were determined by pipetting. The pipette


30

suspensions and sand were oven dried at 105oC for 12hours. A blank sample was also prepared to

check the error committed during the procedure.

The laboratory results were used to cross check field description on soil texture.

Plate 4- 2 Particle size distribution procedure in the laboratory

4.2.4 Land evaluation

(A) Interviews

A main objective of this research was to carry out an evaluation of land in the study area hence

interviews were conducted. Arrangements were made with the Agricultural District Officer to

conduct interviews with smallholder farmers as well as the technical assistants and Soil surveyor

at District level.

Semi-structured questionnaire were prepared during prefield phase (appendix G). Individual

farmers were interviewed at their farmlands. Agricultural extension workers were interviewed to

get information on land use types, land characteristics and severity levels. This information has

been integrated with results from the water balance model and processed using ALES

programme.

(B) Climatic data access

Climatic data for the study area was accessed from Water Resources Programme of ITC. The data

covers a period of 15 years (1986-2001). The data comprised of rainfall, maximum temperature,

minimum temperature, relative humidity, wind speed and sunshine. From this data, only rainfall


31

covered the stated period whilst the rest of parameters were from April 1998 to 2001 for Paje and

Mokongweng stations. The data had some missing variables and this posed a problem in running

PS123 programme.

Due to this problem, parameters from Paje and Mokongweng (stations surrounding Serowe) were

regressed and interpolated to fill gaps in Serowe’s climatic data. In some instances, it was not

possible to regress, as only one set of data was available. This was another hiccup. In order to

solve this problem, another set of climatic data was obtained from FAOCLIM. FAOCLIM is a

set data file that stores climatic data for most of the worlds’ meteorological stations. However,

this FAOCLIM data does not indicate the year for which the data was recorded. From this set of

data, maximum and minimum temperatures of Mahalapye station were extracted and used to fill

in the gaps. The latitude difference between Serowe and Mahalapye is 0.6o so it was assumed that

there would be no major climatic differences.

In addition to this data, another set of data was obtained from Gaborone, Botswana. This data

contained rainfall, relative humidity, maximum and minimum temperature of different stations

from 1998 to 2000. From this data, rainfall was for Serowe, maximum and minimum temperature

for Mahalapye and the rest for unknown stations. Some variables from Serowe and Mahalapye

were used to fill in the gaps. Through this rather complex procedure a climatic file was created.

(C) Production potential PS-2

The PS123 programme requires daily climatic data, generic characteristics of the crop and soil

data. The climatic parameters required are maximum and minimum temperature, rainfall, relative

humidity, potential rate of evaporation, sunshine hours and rate of evapotranspiration.

The files for crop and soil were created based on the crop varieties grown in the area and soil

properties. The model was run from Julian day 306 to Julian day 61 using five different levels of

initial matric suction (PSIint.). The planting date was hypothetically chosen from the information

that was derived from interviews. The PSIint used were 500cm, 1000cm, 1500cm, 2000cm,

2500cm and 3000cm. The surface storage capacity of water was calculated based on the surface

roughness of the farmland and the position on the landscape. The following formula was used for

calculation of surface water storage.


32

)cos(*)cos(*2)(cot)(cot

*)sin(

)(2sin**5.0

PHISIGPHISIGanPHISIGan

SIGPHISIG

drSSC−++−= (4-1)

Where SSC is equivalent to surface storage capacity (cm)

dr is surface roughness or furrow depth (cm) SIG is clod angle or furrow angle (degree) PHI is average slope of the land (degree) (Driessen and Konijn, 1992) It should be noted that only Pe111 (Tread/Riser on higher terrace), Pe112 (Tread/riser on middle

terrace), Pe113 (Tread/Riser on Lower terrace) and Pe115 (Slope floor complex of the Vale) were

evaluated in this programme of PS123 because that is where the farmlands are located.

Apart from running the programme using different initial matric suctions, another scenario was

run that considered late planting by two weeks. The reason behind this was to find out if there

would be differences in yield between early and late planting since most of the farmers plant late.

This was revealed during farmer interviews.

Below are crop characteristics that represent the crop indicative values.

Table 4- 1 The crop indicative values Characteristic Maize Sorghum Photosynthetic mechanism C4 C4 SLA 14-35 11-21 TO oC 10 10 Tsum 1600 1600 ke 0.6 0.6 Tleaf 1000 975 Root depth 100-170 100-120 SLA is specific leaf area, m2 kg-1 TO is threshold temperature of development (oC d) Tsum is heat requirement for full development (oC d) Ke is the extinction coefficient for visible light Tleaf is heat sum for full development of leaf tissue (oC d)


33

(D) Selection of Land use requirements (LURs)

Set of LUR were selected which suits the environmental conditions of the area as well as the land use types according to the list published by FAO (1984) of the suggested land use requirements. These LURs were based on the following criteria:

• Importance (relevance) for use • Spatial variations in the corresponding land quality in the study area • Availability of knowledge with which to evaluate the corresponding land quality • Availability of data with which to evaluate the corresponding land quality

The LURs and LCs were chosen and crosschecked using the information acquired through interviews from the farmers and agricultural extension staff. (See Table 4-2)

Table 4- 2 LURs for maize

Land quality

Diagnostic factor

Factor rating

Highly suitable s1

Mod. Suitable s2

Marginally suitable s3

Not suitable n

Total rainfall in growing season (mm)

>600 400-600 300-400 <300

Textural class SC, VFS, CL FS, SL S C Yield Kg -ha >6000 4000-6000 2000-4000 <2000

Moisture availability

Soil effective depth (cm)

>120 50-120 30-50 <30

Textural class SL, SC, LS, S

SCL, L SiCL, C Rooting conditions


>120 50-120 30-50 <30

Oxygen availability

Soil drainage Excessively drained, well drained

Mod.well drained

Imperfectly drained

Poorly drained

Slope % <3 3-8 9-16 >16 Erosion hazard Erosion class None Moderate Severe very severe Soil workability

Wet consistence class (stickness)

Non-sticky

Slightly sticky

Sticky

Very sticky

Texture class S, LS, SL SCL L, CL _ Sealing hazard Crusts (mm) None <5 5-10 >10


34

Table 4- 3 LURs for sorghum

Land quality

Diagnostic factor

Factor rating

Highly suitable S1

Mod. Suitable S2

Marginally suitable S3

Not suitable N

Total rainfall in growing season (mm)

>500 400-500 250-400 <250

Textural class SL, LS FS, CL S, SCL C, S Yield Kg -ha 3000 2000-3000 1500-2000 <1500

Moisture availability


>170 50-170 50-70 <50

Rooting conditions

Textural class SL, LS, S SCL, L CL C

Soil effective depth

>170 70-170 50-70 <50

Oxygen availability

Soil drainage Excessively drained, well drained

Mod.well drained

Imperfectly drained

Poorly drained

Slope % <3 3-8 9-16 >16 Erosion hazard Erosion class Slight Moderate Severe Very

severe Soil workability

Wet consistence class (stickness)

Non-sticky

Slightly sticky

Sticky

Very sticky

Texture class S, LS, C, SiC, SC

SL, SCL Si, SiL, C Sealing hazard

Crusts (mm) <1 1-2 2-5 >5

(F) Building model in Automated Land Evaluation System (ALES) for Land Suitability Evaluation

The data obtained through interviews during fieldwork was processed and fed into ALES. A

single model called “Botswana Suitability Land Evaluation” was built for both LUTs.

This is the stage by which ALES can assess the suitability of each land-mapping unit. This involves construction of decision trees for each LUR based on expert knowledge. Each LUT has different LURs. The LURs and their diagnostic factors as shown in tables 4-2 and 4-3 were the inputs for construction of decision trees. In this procedure, one land quality would be determined by more than one land characteristic to come up with the severity levels. The decision trees were constructed by matching the LURs and LCs for example; decision tree

for land quality moisture availability was determined by considering diagnostic factors total


35

rainfall in the growing season, the soil depth, the textural class and yield. The major factor is total

rainfall, therefore was at the top of the tree but the amount of water a soil can hold also depends

on soil depth hence soil depth was the second branch. Soil texture plays a role in the moisture

holding capacity of the soil, this factor came at the third branch and then the yield came on the

last branch. These factors were matched against each other to determine the severity level of land

quality soil moisture availability. Below is an example of a decision tree.

LUT 2,Erosion hazard > Slp (Slope) <3 (none) [0-3 %]....... : 1 (none) 3-8 (slight) [3-8 %] > Txc (Textural class) FS (Fine sand) [3-10 c : 2(slight) SL (Sandy loam) [10-15 c : 3 (moderate) LS (Loamy sand) [15-20 c : =2 CL (Clay loam) [20-50 c : =3 (moderate) SCL (Sandy clay loam) [5 : 2 (slight) 9-16 (moderate) [8-16 %] : 3 (moderate) >16 (severe) [16-25 %].. : 4 (severe) The last step was to enter all the map units into database where the severity level was determined

based on the decision trees, which had already been created. At this point, the model was now

ready to compute the evaluation. After computation, the results were reviewed to check for

irregularities and improve the evaluation procedure

Since ALES is not GIS based, the map units were classified using Integrated Land and Water

Information System (ILWIS) programme, a geographical information system. Columns were

added to the histogram of the Geopedological map using the suitability class domain. The

suitability maps were created from attribute map of the geopedological map.

4.3 Data processing and analysis

4.3.1 Statistical analyses

(A) Hydraulic properties

The measurements from field were statistically analysed using Excel, SPSS and R programme (R

Development Core Team, 2002) softwares in order to examine the differences in the strata and

also to evaluate the relationship between them. Parameters like descriptive statistics, correlation

and regression analysis were performed.


36

(B) PS-2 Production Potential water –limited production

The results from PS-2 were regressed using Excel software in order to establish the relationship

between moisture availability and yield. The independent variable (x-axis) was the initial matric

suction and dependent variable (y-axis) was yield (See fig 7-3 –7-6).

Furthermore, the yield was classified into suitability classes and used as a diagnostic factor in

ALES programme. The reason for using two evaluation tools is that PS2 evaluates land based on

water-limited only whilst ALES considers environmental aspects, managerial aspects and soil

characteristics.

4.3.2 Geostatistical analysis

This operation was done in order to examine the spatial variability of soils and soil moisture

distribution as well as producing the soil map. The operation used the Ordinary krigging. The lag

spacing was set at 2000m for both moisture at 10cm depth and 30cm depth. The range was

1700m with a limiting distance of 14000m for moisture at 10cm depth. In case of 30cm depth, the

lag was 2000m, a range of 4000m with limiting distance of 16000m.

Although the sample size was small (56points) the analysis went further to do krigging

to examine the spatial variability.

4.3.3 Remote Sensing

This technique was employed to produce a land use map using ILWIS software. Initially, a map

list of bands 1,2,3,4,5 and 7 from Landsat image was created. From this map list, a sample set

was produced that stores the relevant data regarding input bands, land use classes and background

image for selecting the training areas. A false colour composite (FCC) map was produced from

bands 4,3,2 (4-red, 3-blue and 2-green) and was used as a background image to train the sample

set. A training phase was performed whereby six classes were defined and these are bare sand,

dense vegetation, farmland, Savanna shrub, Savanna trees and settlement. Classification of the

image was done using Minimum Mahalanobis Distance Classifier algorithm.

4.4 Limitations

• The climatic data sets had a lot of gaps.

• With system of operating from three different settlements (cattle post, farmland and

village) it was time consuming to get access to some of the farmers for interviews.


37

Chapter 5 Soils 5.1 Soil and soil formation

Soils are one of the major natural resources that life depends on. Dumanski (1993) describes soil

as a natural body in relation to the factors of soil formation. Soil formation is induced by a

number of factors such as climate, parent material, biological activity and topography (Jenny,

1941).

Development of soil is materialised in the formation of horizons. The soil horizons are layers of

soil or soil material approximately parallel to the land surface and differing from adjacent

genetically related layers.

5.1.1 Climate

Botswana, in particular Serowe area is under semi-desert area, hence climatic factor plays a major

role in soil formation. Daily and seasonal variations coupled with low and irregular rainfall are

responsible for the type of weathering and profile development in general. However, rainfall

effectiveness in terms of infiltration /runoff, temperature and wind are important parameters to

consider when discussing soil formation in the study area.

Wind plays a role more especially in the sandveld where it blows the sands from one place to

another making some depositional aeolian dunes. Despite the strong winds on the sandy material,

a dense vegetation of the area (Savannah bush land with good grass cover) has led to minimal

wind erosion except in the open spaces where vegetation is very scanty or no vegetation at all.

5.1.2 Erosion

Water erosion has played a major part in the peneplain. Soil materials move from the eroded

terrace to the lower glacis of the area resulting in the stratification of horizons as they get

deposited at different time. These materials are unconsolidated which undergo further weathering

(see plates 5-1 and 5-2).


38

Plate 5- 1 A gully showing layers of depositional materials around Sokwe area in

Serowe

Plate 5- 2 Gully formation due to water erosion


39

5.1.3 Vegetation

Although the area is densely vegetated, its role in soil formation is very minimal (subverting wind

erosion). This is due to the small leaf nature of vegetation. The organic matter content is low

ranging from 0.39% top (10cm) in sandveld to 0.65% (Betemariam, 2003) in the hardveld. The

soil structure is not well developed because of the low organic content as explained by Farshad

(1997) that organic matter content of less than 1% is insufficient to promote good soil structure

and cohesion between soil particles, hence, leading to higher susceptibility to soil erosion.

5.1.4 Parent material

The major parent material in the area is sand derived from sandstone and stormberg

Basalt. However, some lime does occur in the peneplain. Most of the soils are formed in-

situ. Alluvial deposits are common in the lower part of the peneplain.

5.2 General description of landforms and soils

A geopedological map (fig 5-2) of the study area was developed with the corresponding legend

upon inferring the available aerial photographs and image interpretation. The area has three main

landscapes (see 3.4) upon which landforms were distinguished. Fig 5-1 shows the points of soil

profile pits within the two blocks.

Pu111 Summit

This is the highest point in the study area. It lies on the bed of Kalahari basin with elevation

ranging from 1200 to 1260m.The map unit is limited by abrupt descent to the lower plains. The

soils are deep to very deep, well to somewhat excessively drained. Three different soils occur in

this landform. The yellowish and grayish soils are on the western part of the plateau where they

are found in strips in the direction of the wind. These soils are formed on aeolian deposits. The

third type occurs near the escarpment and these are yellowish brown (with chroma more than 4)

to yellowish red fine sands. The pH ranges between 4 and 4.5. There is not much distinction in

horizons of the soil profile (see plate 5-3 for soil profiles in the study area). It is flat to

undulating.

Hi111 Slope facet complex This map unit divides the sandveld and the hardveld and stretches northeast to southwest. The

soils are shallow, somewhat excessively drained, yellowish red to yellowish or dark reddish

brown sands and loamy sands. The area is hilly with slope of 10-30%.


40

Hi112 Talus-hillock-complex

The map unit is on the lower part of Hi111 with slope of 0-5%. The soils are moderately deep to

shallow, well to somewhat excessively drained, light yellowish brown to dark grayish brown fine

sands to loamy fine sands (non calcareous between 50-100cm). It is flat to undulating.

Pe111 Tread/riser of Lower terrace

In this map unit, the soils are deep to very deep, poorly to imperfectly drained, dark grayish

brown to very dark gray clay. The slope is within the range of 0-5%. It is the lowest part of the

study area with elevation of 1000m. The area is undulating. It is used for arable cropping. The

soils are compound and have abrupt boundaries. Some lime concretions occur in some parts of it.

Pe112 Middle terrace

The map unit has deep, moderately well drained reddish brown to dark yellowish brown sandy

clayloam to sandyclay. These are alluvial deposits that come from the eroded terrace. They show

lamellae of clay accumulation. The soil is a consociation of Calcic Luvisol. It has a slope of 0-2%

with pH of 7.5. They are used for arable cropping.

Pe113 Tread/riser of Higher terrace

The soils in this map unit are deep to very deep, well to excessively drained, red to yellowish red

loamy fine sands over sand loams. The slope is within the range of 0-5%. The area is flat to

undulating.

Pe114 Tread/riser of Eroded terrace

The map unit is in the centre of the study area. It is highly eroded. The soils are moderately deep

to shallow, moderately well to well drained, dark brown to reddish brown clayloam to clay. It lies

on the basalt basement complex with a few rock outcrops. It is undulating to rolling. This is used

for settlement and commercial purposes.

Pe115 Slope floor complex of the vale

These are incisions that occur at the bottom of the middle terrace. The soils are deep to very deep,

moderately to imperfectly drained, dark grayish brown-to-brown clayloam to clay. The slope is 0-

5%. It is flat to undulating.


41

Pe116 Slope facet complex of the Inselbergs

These are rocky hills that occur on hardveld. They are steep-sided residual hills rising abruptly

from the surrounding erosional peneplain. They occur mostly on the granitic gneiss basement

complex.

Fig 5- 1 Study area showing the sample blocks and pit profile points


42

Plate 5- 3 Ferralic Arenosols and Pellic Vertisols profiles

Fig 5- 2 The geopedological map of Serowe


43

Table 5-1 The geopedological legend Landscape Relief

Type Lithology Landform Map

unit symbol

Slope (%)

Major soils Area (ha)

Plateau Mesa Sand with Silcretes and ferricretes

Summit Pu 111 0-5 Arenosols (Orthoeutric Arenosol Hypoluvic Dystric Arenosol, etc)

163826

Sandstone Slope facet complex

Hi111 10-30 Eutric Arenosol Arenic Luvic Xerosol Ferralic Arenosol Arenic Ferric Luvisol Arenic Ferric Luvisol Calcic Luvisol Orthic Luvisol Chromic Luvisol

13885 Hilland

Hill

Sandstone Talus-hillock complex

Hi 112 0-5 Orthic Luvisol Ferralic Arenosol Arenic Ferric Luvisol Luvic Arenosol Chromic Calcic Luvisol Calcic Eutric Nitosol

4020

Higher Terrace

Residual/unconsolidated Tread/Riser Pe113 0-5 Calcic Luvisol Ferralic Arenosol Arenic Ferric Luvisol Calcic Cambisol Orthic Luvisols Eutric Nitosols Chromic Nitosol Chromic Calcic Luvisol Calcic Gleysol

18124

Middle terrace

Residual/unconsolidated Tread/Riser

Pe112 0-5 Ferralic Arenosol Chromic Luvisol Arenic Calcic Luvisol Eutric Nitosol Calcic Eutric Nitosol

18124

Lower terrace

Residual/unconsolidated Tread/Riser of Pe113 0-5 Pellic Vertisol Ferric Arenosol Chromic Vertisol Calcic Cambisol Orthic Luvisol Chromic Calcic Luvisol

10977

Peneplain

Eroded terrace

Sandstone Eroded terrace Pe114 0-5 Chromic Calcic Luvisol Ferralic Arenosol

4637


44

Vale Residual/unconsolidated Slope floor complex

Pe115 0-5 Arenic Ferric Luvisol Calcic cambisol Ferralic Arenosol Orthic Luvisol Pellic Vertisol

14975

Inselbergs Basalt/Sandstone Slope facet complex

Pe116 Chromic Calcic Luvisols Rock outcrops

221

5.3 Soils of the study area

The study area has four groups of soils (Driessen et al., 1998) namely Arenosols, Regosols,

Luvisols, and Vertisols.

The dominant group is the Arenosols. They are inherent, yellowish red to reddish brown single

grain materials. They are predominantly structureless, non-stick and non-plastic when wet and

loose when dry. These are deep to very deep sands predominantly of Aeolian nature (D. O. S. M,

2001), and excessively to somewhat excessively well-drained soils with an average pH of 4.5.

There are some patches where the soils are just yellowish fine sands. The profiles are quite

uniform throughout the depth. The total fine sands are generally more than 50 percent. Clay and

silt are less than 10 percent (laboratory results).

One strange thing about these sandy soils is the growth of small plants (with shallow rooting

depth) during the hot months yet the moisture content is very low. This suggests that there is

some moisture kept within 10-20cm of the soil profile. In most cases the subsurface horizons are

completely dry. After rains most moisture is available up to 10m deep (D. O. S. M, 2001).

The Luvisols are characterised with crusting which impedes water infiltration. This results in

widespread of sheet erosion in arable fields. They have a pH of 5.5 on average and are well to

somewhat excessively drained. They are occur on the young land surfaces on the lower parts of

the landscapes, in some cases are associated with vertisols.

The Regosols are shallow soils with uncompleted weathered parent material with low infiltration

rates. They are prone to erosion. Regosols form a hard surface early in dry season that (this crust)

hinders emergence of seedlings and infiltration of rain. In general the surface horizon is thin with

very low organic matter content. The soil pH is 7.0. They occur on the peneplain and are used for

grazing livestock.


45

The Vertisols are deep soils characterised by high clay content, usually more than 50% with poor

drainage. Results from particle size distribution analysis indicate a range of 48 to 51% clay

content.

Fig 5-3 shows the soil map of the study area.. It should be noted that the soil map has been

adopted from the original map (De Alwis, 1985). Although some differences were noted in the

field especially in the western part of Pu111 and in map unit Pe111, these could not be added on

the map because data gathered from the field was not enough to effect the change.

Fig 5- 3 The soil map of Serowe


46

Table 5-2 Correlation table between the FAO soil map and geopedological map (presented in this thesis) Symbol Soil Description

Classification Landform

A1 Deep to very deep, poorly to imperfectly drained, dark grayish brown to very dark gray clay. Flat to almost flat

Pellic vertisol, partly sodic

Lower terrace (Pe113)

A2 Deep to very deep, poorly to imperfectly drained, dark grayish brown to reddish brown clay loam to clay Flat to slightly undulating

Chromic Vertisol Lower terrace (Pe113)

A3 Deep to very deep, imperfectly drained dark grayish brown sandy clayloam to clay. Flat to slightly undulating

Vertic Cambisol Middle terrace (Pe112)

A4 Mod. deep to very deep. Imperfectly to mod. Well drained, dark grayish brown to brown sandy loam to sandy clay Flat to slightly undulating

Calcic Cambisol Vale (Pe115)

A4b Mod. deep to very deep imperfectly to mod. Well drained. Dark grayish brown to brown clay loam to clay Flat to undulating

Calcic Cambisol Lower terrace (Pe113) Vale (Pe115)

A4c Mod. deep to very deep, mod. Well-drained grayish brown-to-brown sandy loam to sandy clayloam. Flat to undulating

Calcic cambisol Vale (Pe115)

A9 Deep to very deep, imperfectly to mod. Ell drained, dark brown sandy clay loam to clay Flat to slightly undulating

Calcic Luvisol Middle terrace (Pe112)

A10 Deep to very deep, mod. Well-drained, strong brown to yellowish red sandy loams to sandy clayloams. Flat to undulating

Chromic Calcic Luvisol partly petrocalcic

High terrace (Pe111)

A12 Mod. Deep to deep, well drained, brown to yellowish red loamy sands to sandy loams Almost flat to undulating

Arenic Ferric Luvisol Middle terrace (Pe112)

A13 Mod. deep to deep mod. Well to well drained, dark red to strong brown, sandy loam to sandy clayloam. Almost flat to undulating

Chromic Luvisol Middle terrace (Pe112)

A14 Mod. deep to very deep, mod well to well drained. Dark brown to yellowish sandy loam to sandy clay Flat to undulating

Orthic Luvisol Middle terrace (Pe112)

A16 Very deep., mod. Well to well drained, dark red to strong brown, sandy loam to sandy clayloam. Almost flat to undulating.

Eutric Nitosol Middle terrace (Pe112) High terrace (Pe111)

A16a Very deep, imperfectly to mod. Well-drained, dark red to dark brown sandy clayloam to clay strongly calcareous and often with dark grayish brown top layer. Flat to almost flat.

Calcic Nitric Nitosol Middle terrace (Pe112)

A19 Deep to very deep well to somewhat excessively drained, dark red to brown sands to loamy sands Almost flat to slightly undulating

Ferralic Arenosol

Lower terrace (Pe111)

A30 Deep to very deep imperfectly to poorly drained (very) dark gray sandy clay to clay. Flat

Calcaric Gleysol Sodic High terrace (Pe111)

B1 Very shallow to shallow, well to somewhat excessively drained, reddish brown to dark brown sandy loam to clay loam Undulating to hilly

Eutric Regosol Slope-facet complex Hi111

B5 Mod. deep to deep, mod well to well drained, reddish brown to strong brown sandy clay loam to clay Undulating to rolling on basalt

Chromic Luvisol Slope-facet complex

B5a Shallow t mod deep, well drained reddish brown to strong brown sandy clay loam to sandy clay Undulating to rolling (mainly on basalt)

Chromic Luvisol Partly petric, some lithic

Vale (Pe115)

B6 Mod. deep to deep, mod. well to well drain, dark brown to reddish brown clayloam to clay. Undulating to rolling (basalt)

Calcic Luvisol Eroded terrace (Pe114)


47

D9 Deep, mod, well drained, reddish brown to dark yellowish brown sandy

clay loam to sandy clay Flat to undulating

Calcic Luvisol Middle terrace (Pe112)

S1 Very shallow to shallow, excessively drained yellowish red to yellowish brown sands and loamy sands Undulating to hilly

Ferralic Arenosol Lithic

Slope-facet complex Hi111

S1a Moderately deep, somewhat excessively drained, yellowish red to yellowish or dark reddish brown sands and loamy sands. Undulating to hilly

Ferralic Arenosol Slope facet complex (Hi111)

S3 Deep to very deep, well to somewhat excessively drained, yellowish brown (but with chroma of more than 4) to yellowish red fine sands. Flat to undulating

Ferralic Arenosol Summit (Pu111)

S5 Deep to very deep, well to somewhat excessively drained, red to strong brown fine sands to loamy fine sands Flat to undulating

Ferralic Arenosol Middle terrace (Pe112) High terrace (Pe113)

S5a As S5, but showing lamellae of clay accumulation Luvic Arenosol Middle terrace (Pe112)

S6 Deep to very deep, somewhat excessively to excessively drained, red to yellowish brown fine sands and loamy fine sands. Undulating to rolling dunes

Ferralic Arenosol Middle terrace (Pe112)

S7 Deep to very deep, well to somewhat excessively drained, red to strong brown loamy fine sand. Flat to undulating

Arenic Ferric Luvisol Middle terrace (Pe112)

S10 Deep to very deep, well to excessively drained, red to yellowish red loamy fine sands over sand loams Flat to undulating

Arenic Ferric Luvisol High terrace (Pe111)

S16 Deep to very deep, somewhat excessively drained, light yellowish brown to dark grayish brown fine sands to loamy fine sands Flat to undulating

Dystric Arenosol Vale (Pe115)

S17 Deep to very deep, well to somewhat excessively drained, light yellowish brown to dark grayish brown fine sands to loamy fine sands (non calcareous between 50 and 100cm)

Eutric Arenosol Talus-hillock complex (Hi112)

Note: Ks = soils on coarse-grained sedimentary rocks R = very shallow soils on steep hills, ridges and escarpments Adopted from: Soil Mapping and Advisory Service Project BOT/80/003


48

Chapter 6 Land use 6.1 Land use definiton and kinds of land use

Land use is the activity that is carried out on a piece of land for a certain period of time. It may

change with time from one land use to another. However the concept of land use is too wide to be

useful except in very general analyses(Driessen and Konijn, 1992).The major kinds of land use

are rainfed agriculture and grazing whilst irrigated agriculture is at a very small scale. Land use in

Serowe is also influenced by settlement. The major settlements are found along the base of the

scarp. The concentration here, according to senior residents, owes much to the existence of

ephemeral springs in the former years. Although these no longer flow, abandoned spring

discharge points can still be seen at Serowe and Paje (SGC, 1988). Fig 6-1 shows the land

use/land cover for the area.

Fig 6- 1 Land use map of Serowe


49

6.2 Land utilisation types in the Serowe area

As “land use” is too wide a concept to be useful in land evaluation, land utilisation type (LUT)

was introduced which is more specific. It is characterised by its key attributes like biological,

socio-economic and technical aspects of land use that are relevant to functioning of it (Driessen

and Konijn, 1992)

In Serowe area, there are a number of LUTs that are practised and these are as follows;

traditional rainfed maize, traditional rainfed sorghum, traditional millet, traditional,

mechanised rainfed maize, irrigated vegetables, orchards and traditional cattle ranching.

A cattle rearing is the biggest enterprise in the area. The land parcels are commonly called cattle

posts. There are no paddocks to limit mobility of cattle during grazing. The herdsmen have to

drive cattle to the drinking places that are improvised by borehole at the cattle posts.

As the interest of this research was on smallholder farmers who grow rainfed crops, LUTs

traditional rainfed maize and traditional rainfed sorghum were chosen, as they are major cereal

foods in the area and in Southern region as a whole. The two LUTs are sometimes grown under

mixed cropping but majority of the farmers that were interviewed practise single cropping

systems.

The area of farmland ranges from 4ha to 10ha. For those with greater than 4ha do not use the

whole land at one growing season due to problems of acquiring farm inputs such that part of the

land remains idle. This indirectly leads to fallowing of the land although it is not their intention to

do so. All the farms are well fenced to protect the crops from destruction by grazing animals. The

rains start in November and end in April and harvesting is done in May/June when crops have

completely dried (see table 6-1). This crop calendar was captured during the interviews with

farmers in the study area. The hypothetical dates for planting were chosen based on this calendar.

Table 6- 1 Crop calendar Months Activity Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Land preparation & seeding

Weeding Harvesting


50

There are specific varieties that are grown for one main reason of early maturity, as the rains are

very erratic. The varieties for maize are Kgalagadi, Porch pearl and R201, all mature within the

range of 120-125 days. Farmers use a seed rate of 7kg -ha (calculated from the results of farmers

interviews) yet the recommended rate is 10kg -ha for row planting and 20kg -ha for broadcasting.

As for sorghum, the varieties are Phofu (red in colour) and Segaolane (white in colour). Phofu

takes 115 to 125 days and Segaolane matures within the range of 125 to 130 days.

According to results of the farmers’ interviews, the management of the farms is generally poor.

Land preparation and planting are done simultaneously as the farmers wait until the rains come.

The seed is mostly recycled from the previous harvest.

Description of land utilisation types (LUTs)

The selection of land use types depends on the local resources situation. The land use types in the

area are maize, sorghum, millet, cowpeas and cattle raise-based. Obviously the climatic condition

of the area is an important and decisive factor why these types are practised.

The selected land use types in this study are rainfed maize and sorghum under traditional

management. Since these LUTs are traditionally managed, the inputs are low with low degree of

management. For these low inputs, the farmer does not apply anything to improve the quality of

land therefore; it is not strange that farmers in the area experience low yields.

LUT1 Maize-based

This is a rainfed traditionally managed land use type. The family members provide labour but

during peak periods of weeding, casual labour is employed. It should be noted that only those

families that can afford to pay for casual labour do employ it. Main source of power is animal

draught except for a few farmers who use tractors for ploughing and planting only. The seed is

broadcasted on the same day of ploughing the field, at rate of seven kilograms per hectare. The

farmers have access to reasonable agricultural services. The main variety grown is Kgalagadi,

which takes 125 days to reach maturity with plant population of 10,000per hectare. In all the

farmlands visited no fertiliser is applied to the crops.

Sometimes the crop is attacked by stalkborers but there is no control measure. Farmers do not

practice any soil and water conservation measures.


51

LUT2 Sorghum-based

This is also rainfed traditionally managed land use type. The family members provide labour but

during peak periods of weeding, casual labour is employed. Main source of power is animal

drought except for a few farmers who use tractors for ploughing and planting only. The seed is

broadcasted on the same day of ploughing the field, at rate of five kilograms per hectare. The

farmers have access to reasonable agricultural services. The preferred variety is Phofu (red

sorghum), which takes 115 to 125 days to reach maturity with plant population of 40,000 per

hectare. In all the farmlands visited no fertiliser is applied. Crickets, aphids and birds mainly

attack sorghum. The birds are the most serious pests of sorghum and if left unattended to, the

production is drastically reduced to zero. There is no control for crickets and aphids but scaring

them away controls birds.

Below are tables showing the differences in yield between the actual and potential for both early

and late planting. The actual yields are calculated from the yields obtained during interviews with

farmers whilst the potential yields are the results from PS2 water- limited production potential

(see tables 6-2 to 6-5).

Table 6- 2 Yield gap for LUT1 in 1999/2000

Mapping units Actual yield Water-limited yield Yield gap

Pe111 96 6072 5976

Pe112 & Pe113 219 5754 5535

Pe115 317 1606 1289

Table 6- 3 Yield gap for LUT2 in 1999/2000 growing season


Pe111 305 1420 1115

Pe112 & Pe113 219 1268 1049

Pe115 105 1115 1050


52

Table 6- 4 Yield gap for late planting for LUT1


Pe111 96 5853 5757

Pe112 & Pe113 219 5455 5236

Pe115 317 1257 940

Table 6- 5 Yield gap for late planting for LUT2


Pe111 96 1219 914

Pe112 & Pe113 219 1021 802

Pe115 317 1008 903

The yield gap is very wide due to a number of reasons:

Late land preparation as the farmers wait for the rains to come. The seed rate used by farmers is

too low to produce good yield since plant population is also reduced. The recommended seed

rates are 20kg –ha for maize and 10kg –ha for sorghum. Farmers never apply fertilizer to their

crops to boost plant growth. Although nutrient test was not conducted in the area during

fieldwork, the soils are not fertile enough to produce good yield. Literature on crop production in

the area indicates that fertilizing the crops either in organic form or inorganic form is necessary

for better output (Gibbon and Pain, 1985; Nampad, 2000)

Weeding is done only once, which gives chance for the weeds to compete favourably with the

crops.

Farmers do not practise soil and water conservation measures that would assist in minimising

water runoff and encourage infiltration as revealed from interviews. Since some farms are on

sloping areas this water runoff also carries away fertility of the soil.

Control of pests is minimal especially for sorghum, which is highly susceptible to attack by birds.

Labour to scare these birds are rarely found as it used to be in the past years when children were

used. Nowadays, children are encouraged to go to school hence there is no one to attend to the

crops.


53

As observed from tables 6-2 to 6-5, the yields are too low to offset the cost of growing these

crops. The currency is in Pulas (P). The cost of maize seed is P3 per 10kg bag. On average the

area planted is 4ha and making a total of P12. Casual labour is P5 per day per person and on

average one employs 3casual labourers, which gives a total of P45. Total expenditure is P57. This

gives a negative gross margin of P57 since the yield is not sold but rather consumed by the family

members.


54

Chapter 7 Results and Discussion 7.1 Hydraulic properties

This section describes the results got from measurements of hydraulic properties and their relationships.

7.1.1 Infiltration rates

Below is fig 7-1 showing the infiltration rates over time that was measured in the field.

In some sites, at first the water intake was high (7-1a) and dropped with time until the base

infiltration rate was reached whilst in other sites, the initial intake was low (7-1b) but increased

with time, then dropped until it reached the base infiltration rate. This can be attributed to the

status of the surface features of the sites. In cases where there was leaf litter and a lot of cow dung

on the surface, initial intake was high as opposed to surfaces without any litter.

It should be noted that the graphs are not smooth and this is probably due to the fact that in the

process of infiltration, the water intake is not always in the order of decreasing at a decreasing

rate but rather it fluctuates as water enters the soil until it stabilises. (See appendix A for the

results of measurements)

Fig 7- 1Basic infiltration rates

(a)

0

20

40

60

80

0 5 10 15 20

Time

Infil

trat

ion

(b)

0

20

40

60

0 5 10 15

TimeIn

filtr

atio

n

EPT 01 SVD 081


55

Table 7- 1 Descritpive statistics for infiltration between landscapes

STRATUM Variable Minimum Maximum Mean Std. Deviation

Sandveld (Plateau) Infiltration rate 18.5 47.5 22.99 8.9 Escarpment (Hilland) Infiltration rate 8.3 36.2 18.37 7.25 Hardveld (Peneplain) Infiltration rate 6 18 14.43 8.3

Results from descriptive statistics indicate that soils from plateau area have highest infiltration

rates and those of peneplain have the lowest rates. There are variations in all the three landscapes

and the widest variations occur in the peneplain. This can be attributed to different soil types

found in the landscape. There are Arenosols, Luvisols, Regosols and vertisols, which have

different infiltration rates. Another reason could be due to different position in the landscape as

soils on the plateau are different from soils on the slope facet complex due to soil forming factors.

Variations in the plateau area can be attributed to fine sands as well as very fine sands occurring

in the area. Also the clay percent in these soils is different. The clay percent ranges from 3% to

8% of the first 10 to 20 cm of the soil profiles. Joshua (1991) explains that infiltration rates can be

variable for a textural class. In his findings, the Arenosols had a range of 18.5 to 54.3cm/hr from

the same study area.

There are differences in these rates and to see the significance of their differences an ANOVA

table was calculated (see table 7-2 below). The proportion of different soil particle size fractions

influences the pore size distribution, which in turn determines the infiltration rates.

Table 7- 2 ANOVA for infiltration between landscapes

SS df MS F Sig. Infiltration rate Between landscapes 979.2219 2 489.6109 6.98397 0.000 Within landscapes 6870.286 98 70.10496 Total 7849.508 100

The differences between the landscapes and within each landscapes are highly significant

(P=0.000).

The analysis went further to look at differences in soil type. Table 7-3 shows the ANOVA table for differences between point pairs of the soil types.


56

Table 7- 3 ANOVA for infiltration between soil types

Df SS MS F-value P Soil type 4 1687.57 421.89 7.3009 0.000112 Residual 48 2773.75 57.79

The ANOVA for differences between pairs of soil types indicate that there is high significant difference between the means of the pairs of soil types.

Note: FA is Ferralic Arenosols; OL is Orthic Luvisols; CL is Chromic Luvisols; PV is Pellic Vertisols and VC is Vertic Cambisols. The means between Pellic Vertisols and Calcic Luvisols, Pellic Vertisols and Ferralic

Arenosols, Vertic Cambisols and Ferralic Arenosols and Pellic Vertisols and Orthic

Luvisols are significantly different (95%) (Tukey HSD) but there is no significant

difference between Vertic Cambisols and Chromic Luvisols and Vertic Cambisols and

Orthic Luvisols. Considering the upper and lower limits of these differences, an overlap

that includes a zero between the lower and upper limits indicates that the means are

significantly different.

These results imply that there are variations in the soil properties that led to such

differences in behaviour. These variations are probably due to the texture of soils and

organic matter as Dingman (1993) explains that soil texture and organic matter are some

of the factors that influence infiltration of fluids in the soil.

Table 7- 4 Differences between pairs of means of soil types

Soil type Mean StdevVC 9.757143 4.238261PV 12.74444 6.389271OL 26.875 10.62022FA 22.40385 8.459432CL 13.9875 5.736708

Infiltration ratesDifference L-limit U-limit

FA-CL -2.6297 -6.7791 1.5198OL-CL -2.4393 -8.5471 3.6686PV-CL 6.0634 1.1153 10.9744VC-CL 2.1428 -3.0660 7.3517OL-FA 0.1904 -5.0434 5.4242PV-FA 8.6932 4.9243 12.4619VC-FA 4.7725 0.6230 8.9220PV-OL 8.5028 2.6468 14.3587VC-OL 4.5822 -1.5257 10.6900VC-PV -3.9206 -8.8316 0.9903


57

7.1.2 Actual moisture content

The moisture results are not due to rainfall differences since the area did not receive any rains during the period of moisture measurements. Below is analysis of variance table (table 7-5) for the measurements of actual moisture content based on landscape.

Table 7- 5 ANOVA for moisture content between the landscapes

SS df MS F Sig. AMC at 10cm Between landscapes 456.2632 2 228.1316 12.4047 0.000 Within landscapes 1802.292 98 18.39074 Total 2258.555 100 AMC at 30cm Between landscapes 350.2463 2 175.1232 10.69507 0.000 Within landscapes 1604.67 98 16.37419 Total 1954.917 100

There is high significant difference in the moisture content between the landscapes (99%

level). The differences are higher at 10cm depth than at 30cm depth. The F-values are

high (12.4 and 10.69) meaning that there are high variations in the moisture content

between the landscapes. Table 7-6 shows the descriptive statistics.

Table 7- 6 Descriptive statistics for moisture between landscapes

STRATUM Variable Minimum Maximum Mean Std.

Deviation Sandveld (Plateau) AMC at 10cm 0.72 7.45 3.23 2.03 AMC at 30cm 0.22 5.11 2.12 1.33 Escarpment (Hilland) AMC at 10cm 1.06 20.92 8.55 5.77 AMC at 30cm 1.19 13.56 7.08 4.66 Hardveld (Peneplain) AMC at 10cm 0.38 9.6 5.00 3.05 AMC at 30cm 0.44 13.56 6.61 4.18

Soils in the hilland had the highest moisture content at both depths of 10cm and 30cm followed

by peneplain and the last being plateau area. The standard deviation is also high in the hilland,

which implies that there is a wide variation in the soil properties.

The field measurements were further analysed based on soil type as shown in table 7-7


58

Table 7- 7 ANOVA for differences between pairs of soil types

Actual moisture at 10cm depth Df SS MS F-value P Soil type 4 565.25 141.31 11.953 0.000 Residual 48 567.46 11.82 Actual moisture at 30cm depth Df SS MS F-value P Soil type 4 647.26 161.81 24.663 0.000 Residual 48 314.93 6.56

There is high significant difference between the means in soil types (table 7-7). The F-

values are high signifying wide variations in the actual moisture content between the soil

types. Below is table 7-8 showing the means and standard deviations of these soil types.

Table 7- 8 Means and standard deviations of the soil types

At 10cm depth At 30cm depth Soil Type Mean STDEV Soil Type Mean STDEV

Ferralic Arenosol 3.058 2.187 Ferralic Arenosol 2.073 1.642

Chromic Luvisol 6.829 2.308 Chromic Luvisol 8.614 4.432

Vertic Cambisol 11.01 5.306 Vertic Cambisol 10.07 1.316

Pellic Vertisol 7.911 0.998 Pellic Vertisol 11 3.693

Orthic Luvisol 3.775 3.197 Orthic Luvisol 1.6 0.271 The Vertic Cambisols had highest mean (11.01) as well as standard deviation (5.306) at 10cm

depth whilst Pellic Vertisols had highest (11) with Calcic Luvisols having the highest standard

deviation (4.432) at 30cm depth. These variations indicate that the soils have different properties

and behaviour.

In order to examine the differences in pairs of soil types, the confidence intervals were calculated

for each pair (table 7-9).


59

Table 7- 9 The confidence intervals of the soil types

Moisture at 10cm depth Moisture at 30cm depth Soil type Difference Lower limit U-limit Soil type Difference L-limit U-limit FA-CL -2.6296 -6.7791 1.5198 FA-CL -6.1390 -9.2302 -3.0478 OL-CL -2.4393 -8.5471 3.6686 OL-CL -7.2428 -11.7930 -2.6927 PV-CL 6.0634 1.1526 10.9744 PV-CL 1.0016 -2.6569 4.6601 VC-CL 2.1428 -3.0660 7.3517 VC-CL 1.0571 -2.8233 4.9375 OL-FA 0.1904 -5.0434 5.4242 OL-FA -1.1038 -5.0029 2.7952 PV-FA 8.6932 4.9244 12.4619 PV-FA 7.1406 4.3330 9.9482 VC-FA 4.7725 0.6230 8.9220 VC-FA 7.1961 4.1049 10.2874 PV-OL 8.5028 2.6469 14.3587 PV-OL 8.2444 3.8819 12.6069 VC-OL 4.5821 -1.5257 10.6900 VC-OL 8.3000 3.7498 12.8502 VC-PV -3.9206 -8.8316 0.9903 VC-PV 0.0556 -3.6029 3.7140

There is significant difference (99%) confidence interval (Tukey HSD) between means for soil

type pairs Pellic Vertisols and Chromic Luvisol, Pellic Vertisols and Ferralic Arenosols, Vertic

Cambisols and Ferralic Arenosols and Pellic Vertisols and Orthic Luvisols at 10cm depth whilst

at 30cm depth, they are Ferralic Arenosols and Chromic Luvisols, Orthic Luvisols and Chromic

Luvisols, Pellic Vertisols and Ferralic Arenosols, Vertic Cambisols and Ferralic Arenosols and

finally Vertic Cambisols and Orthic Luvisols. The difference between Orthic Luvisols and

Ferralic Arenosols is not significant.

7.1.3 Hydraulic conductivity (k)

The inverse auger hole measurements were calculated and below is an example of the saturated

hydraulic conductivity over time. Amongst the soil types occurring in the area, Arenosols had the

highest hydraulic conductivity. This owes to the fact that large continuous pores have a lower

resistance to flow (and thus a higher conductivity) than or discontinuous pores (Irvine et al.,

2001).


60

INVERSE AUGER METHOD

1.70

1.75

1.80

1.85

1.90

0 200 400 600

Time [sec]

[h+r

/2] (

log)

Kshat=397.4cm -d

Fig 7- 2 Saturated hydraulic conductivity at SVD 081

The calculated results were further analysed to find out the differences between the landscapes and also between the soil types. Table 7-10 shows the ANOVA for hydraulic conductivity between the landscapes

Table 7- 10 ANOVA for hydraulic conductivity based on landscapes

SS df MS F Sig

Hydraulic conductivity Between landscapes 657237.5 2 328618.7 11.88 0

Within landscapes 2711456 98 27667.92 Total 3368694 100 There is significant difference between the landscapes (99%). But to have a better understanding

of this variable, the computed means are displayed in table 7-14.

Table 7- 11 Descriptive statistics for saturated hydraulic conductivity

STRATUM Variable Minimum Maximum Mean Std.

Deviation Sandveld (Plateau) Hydraulic conductivity 99.4 844.6 301.65 232.50

Escarpment (Hilland) Hydraulic conductivity 9.9 695 193.49 176.92 Hardveld (Peneplain) Hydraulic conductivity 9.9 397.4 82.71 108.02

The descriptive statistics indicate that hydraulic conductivity in the plateau area is highest

followed by hilland and the least being the peneplain. The standard deviation follows the same


61

trend. There is wide variation of saturated hydraulic conductivity in the plateau area due to

different particle size of the sands in the area. There are fine sands as well as very fine sands and

in some instances, there are loamy sands.

The means and standard deviations were calculated for the soil types in the area table 7-12.

Table 7- 12 Means and standard deviations of soil types

Soil type Mean STDEV Pellic Vertisols 75.2 151.98

Vertic Cambisols 104.85 119.26 Orthic Luvisols 188.8 173.51

Ferralic Arenosols 291.88 224.44 Calcic Luvisols 77.3 84.37

The Ferralic Arenosols have highest mean (291.8) and standard deviation (224.4) and these are

significant (99%) as shown in table 7-13. The reason for this high standard deviation can

probably be due to the variation of the size of the sand particles in this soil. In some cases there

are very fine sand to fine sand whilst in other cases there are fine sandy loam. This is supported

by Irvine (2001) who came into conclusion that hydraulic conductivity is a highly variable soil

property.

The ANOVA was calculated for the means of the soil types (table 7-13) whilst table 7-14 shows

the confidence intervals.

Table 7- 13 The ANOVA for the means of saturated hydraulic conductivity

Df SS MS F-value P Soil type 4 515440 128860 3.6643 0.01104 Residual 48 1687981 35166

Although the F-value is low (3.66) the difference is significant.


62

Table 7- 14 Differences in the means of saturated hydraulic conductivity of different soil types.

Hydraulic conductivity Soil type Difference L-limit U-limit

FA-CL 214.584 -11.7285 440.8977 OL-CL 133.85 -199.274 466.9739 PV-CL 27.555 -240.286 295.3972 VC-CL -2.1 -286.189 281.989 OL-FA -80.7346 -366.186 204.7169 PV-FA -187.029 -392.578 18.5195 VC-FA -216.685 -442.998 9.6285 PV-OL -106.294 -425.675 213.0864 VC-OL -135.95 -469.074 197.1739 VC-PV -29.6556 -297.497 238.1861

Although the means show differences, these are not significant. The lower and upper limits

overlap each other and include a zero, which implies that they are not significantly different.

7.1.4 Relationship of the hydraulic properties.

In order to evaluate the relationship of these hydraulic properties, correlation was done based on all observations, landscapes and soil type. Table 7-15 shows the correlation of hydraulic properties across the area.

Table 7- 15 Correlation of hydraulic properties across the area

AMC at 10cm AMC at 30cm Hydraulic (k) Infiltration rate

AMC at 10cm Pearson Correlation 1 Sig. (2-tailed) AMC at 30cm Pearson Correlation 0.6757** 1 Sig. (2-tailed) 8.43E-16 Hydraulic (K) Pearson Correlation -1.96E-01* -0.3622** 1.0000 Sig. (2-tailed) 4.96E-02 0.00019721 Infiltration rate Pearson Correlation -2.74E-01** -0.5374** 0.5368** 1.0000 Sig. (2-tailed) 5.54E-03 6.74023E-09 0.0000 AMC is Actual Moisture content ** Correlation is significant at the 0.001level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) The results show that AMC at 10 and 30cm are highly correlated (0.001 level), hydraulic

conductivity and AMC at 10 and 30cm depth are correlated (0.05level), infiltration and AMC at


63

10 and 30cm depth; infiltration and hydraulic conductivity are highly correlated (0.001level)

(table 7-15). Based on these correlations, the analysis went further to perform regression analysis.

Figure 7-3 shows the results of regression analysis across the area.

Fig 7- 3 Hydraulic properties across the area

(a)

Across the area y = -0.6103x + 21.85R2 = 0.1008

0

20

40

60

0 5 10 15 20 25

AWC at 10

Infil

trat

ion

cm-h

r

(b)


01020304050

0 5 10 15 20 25

AWC at 30

Infil

trat

ion

cm-h

r

(c)

Across the areay = -10.805x + 252.51

R2 = 0.064

0

500

1000

0 5 10 15 20 25

AWC at 10

Hyd

raul

ic

cond

uctiv

ity c

m-d

(d)


0

500

1000

0 5 10 15 20 25

AWC at 30

Hyd

raul

ic

cond

uctiv

ity

(e)

Across the area y = 10.848x - 8.3023R2 = 0.2382

0200400600800

1000

0 10 20 30 40 50

Infiltration cm-hr

Hyd

raul

ic

cond

uctiv

ity c

m-d


64

There is weak negative relationship between AMC at 10 and 30cm respectively (7-3a and

b) and infiltration with R2=0.29. Again there is a weak negative relationship between

AMC at 10 and 30cm and hydraulic conductivity (7-3 c and d). But the relationship is

significant (0.001 and 0.05 levels) as observed in table 7-15. As for infiltration and

hydraulic conductivity, the relationship is positive. In all the cases, the R2 is not

explaining much of the relationships, which means that there are other factors that come

into play.

Correlation of hydraulic properties between landscapes was calculated and presented in

table 7-16 and regression was calculated based on the significance of the correlation (fig

7-4)

Table 7- 16 Correlation of hydraulic properties by landscape

Landscape Variable AMC at 10 AMC at 30 Hydraulic Infiltration rate Plateau AMC at 10 Pearson Correlation 1.00

(Sandveld) Sig. Level AMC at 30 Pearson Correlation 0.04 1.00 Sig.level 0.86 Hydraulic (k) Pearson Correlation -0.29 -0.14 1.00 Sig. level 0.22 0.58 Infiltration rate Pearson Correlation -0.02 -0.24 0.19 1.00 Sig. level 0.94 0.32 0.44

Hilland AMC at 10 Pearson Correlation 1.00 (Escarpment) Sig. level

AMC at 30 Pearson Correlation 0.61* 1.00 Sig.level 0.00 Hydraulic (k) Pearson Correlation -0.11 -0.17 1.00 Sig. level 0.48 0.29 Infiltration rate Pearson Correlation -0.20 -0.50 0.43* 1.00 Sig.level 0.20 0.00 0.00

Peneplain AMC at 10 Pearson Correlation 1.00 (Hardveld) Sig. level

AMC at 30 Pearson Correlation 0.91* 1.00 Sig. level 0.00 . Hydraulic (k) Pearson Correlation -0.70 -0.69* 1.00 Sig. level 0.00 0.00 . Infiltration rate Pearson Correlation -0.65* -0.60* 0.82* 1.00 Sig. level 0.00 0.00 0.00 .

* Correlation is significant at the 0.001 level (2-tailed)


65

From table 7-16, hydraulic properties in the plateau area show no significant correlation ;

in hilland, AMC at 10 and 30cm depth (61%) and infiltration rate and hydraulic

conductivity are correlated (43%). In the peneplain , all the hydraulic properties are

highly correlated. Based on those that are significantly correlated, a regression analysis

was performed (see fig 7-4 and 7-5).

Fig 7- 4 Relationship of hydraulic properties in hilland

Hilland y = -0.3653x + 22.013R2 = 0.0829

010203040

0 5 10 15 20

AWC at 10

Infil

trat

ion

cm-h

r

(b)

Hillandy = -0.8713x + 24.909

R2 = 0.3058

010203040

0 5 10 15 20

AWC at 30In

filtr

atio

n cm

-hr

(a)

(c)

Hilland y = 10.943x - 4.0861R2 = 0.2034

0

200

400

600

800

0 10 20 30 40

Infiltration cm-hr

Hyd

raul

ic c

m-d


66

The relationship between AMC at 10 cm depth and infiltration (7-4a) is negative and very

weak (R2 =0.08), the same with 30cm depth (R2 =0.31) but the relationship is significant

(0.001 level). This implies that the less the moisture the soil has, the higher the

infiltration. There is positive relationship between infiltration and hydraulic conductivity.

The lower the infiltration rates the lower the hydraulic rates.

Fig 7- 5 Relationship of hydraulic properties in peneplain

(a)

Peneplainy = -1.2689x + 19.333

R2 = 0.4443

0102030

0 5 10 15 20

AWC at 10

Infil

trat

ion

cm-h

r

(b)

Peneplain y = -0.8093x + 18.298R2 = 0.3417

0

10

20

30

0 5 10 15 20

AWC at 30In

filtr

atio

n cm

-hr

(c)

Peneplain y = -19.143x + 168.05R2 = 0.4446

0100200300400

0 5 10 15 20

AWC at 10

Hyd

raul

ic

cond

uctiv

ity c

m-d

(d)

Peneplain y = -11.441x + 131.72R2 = 0.7209

050

100150200

0 5 10 15 20

AWC at 30

Hyd

raul

ic

cond

uctiv

ity c

m-

d

Peneplainy = 9.2968x - 51.775

R2 = 0.4045

0100200300400

0 5 10 15 20 25

Infitration rate (cm-hr)

Hyd

raul

ic

cond

uctiv

ity (c

m-

d)


67

Again, the trend is the same as in the hilland; the relationship is negative for AMC and

infiltration at both depths but the R2 improves to 44 and 34% respectively (7-5a and b)

and for AMC and hydraulic conductivity improves to 44 and 72% respectively (7-5 c and

d). This shows that soils in different landscapes have different properties; hence,

landscape has an influence on the relationship of the hydraulic properties.

Finally, the correlation was calculated based on soil type as shown in table 7-17.

Table 7- 17 Correlation of hydraulic properties for soil types AMC at 10 AMC at 30 Hydraulic k Infiltration

AMC at 10 Pearson Correlation 1 Sig. (2-tailed)

AMC at 30 Pearson Correlation 0.6784** 1 Sig. (2-tailed) 0.000

Hydraulic k Pearson Correlation -0.2514 -0.4643** 1 Sig. (2-tailed) 0.0694 0.0005

Infiltration Pearson Correlation -0.2432 -0.5585** 0.5301** 1 Sig. (2-tailed) 0.0793 0.000 0.000

From table 7-17, the results show that AMC at 10cm is highly correlated with AMC at

30cm; AMC at 30cm is highly correlated with hydraulic conductivity; AMC at 30cm is

highly correlated with infiltration and hydraulic conductivity is highly correlated with

infiltration. It is from these correlated variables that regression analysis was performed.

Fig 7-6 shows the relationship of the hydraulic properties by soil type.


68

Referring to fig 7-6,in Orthic Luvisols, there is a strong positive relationship between

AMC at 10cm depth and infiltration (R2=0.98); a mild relationship between AMC at

10cm depth and hydraulic conductivity (R2=0.68) and a good relationship between

infiltration and hydraulic conductivity (R2=0.785). These relationships are highly

significant (99%). As for Pellic Vertisols, the relationship between AMC at 10cm is very

strong (R2=0.88) and good relationship between infiltration and hydraulic conductivity

Fig 7- 6 Relationship of hydraulic properties per soil type

(a)

Orthic Luvisols y = 3.2917x + 14.449R2 = 0.982

020

4060

0 5 10

AMC at 10cm

Infil

trat

ion

(cm

/hr)

(b)

Orthic Luvisolsy = 49.612x + 23.865

R2 = 0.6835

0

200

400

600

0 5 10

AMC at 10cm

Hyd

raul

ic

cond

uctiv

ity

(cm

/d)

(c)

Orthic Luvisolsy = 16.007x - 219.04

R2 = 0.7851

0100

200300

400500

600

0 20 40 60

Infiltration (cm/hr)

Hyd

raul

ic

cond

uctiv

ity

(cm

/d)

(d)

Pellic Vertisolsy = 0.9434x + 2.4825R2 = 0.8826

0

10

20

30

0 10 20 30

AMC at 10cm

Infil

trat

ion

rate

(e)

Pellic Vertisols y = 14.86x - 84.53R2 = 0.6338

0100200300

400

0 10 20 30

Infiltration (cm/hr)

Hyd

raul

ic

cond

uctiv

ity

(cm

/d)

(c)


69

(R2=0.63). These high values of R2 are explaining more of the relationship implying that

they affect each other and the remainder could be factors that were not dealt with in this

research.

It should be noted that the sample size for observation per soil type was not adequate to make concrete conclusion, however, it was worth analysing it to examine their relationship. General summary The results from regression of actual moisture content and infiltration rate indicate that there is a

weak negative relationship since the correlation is very low. But the relationship is significant

(99%) level. This implies that when a soil is moist, infiltration is lower than when the soil is dry.

Since infiltration is influenced by a number of factors like texture, crust, organic matter content,

porosity, compaction and structure apart from moisture content ((Dingman, 1993; USDA, 1998)

this explains the reason why the R2 is low in all categories. It is explaining only 10 and 29% (at

10cm and 30cm respectively) across the study area (fig 7-3), 8 and 31% in hilland (fig 7-4) and

44 and 34% in the peneplain (fig 7-5). However, the relationship is positive in the category of soil

type 98 and 68% for Orthic Luvisols and 88 and 63% for Pellic Vertisols (fig 7-6). The remainder

is explained by other factors, which were not dealt with during this research such as porosity,

compaction and structure.

The relationship between actual moisture content and hydraulic conductivity is also negative with

R2 of 6% and 15% respectively across the area (fig 7-3) but it is significant at 99% implying that

the less the moisture in the soil the higher the saturated hydraulic conductivity. The relationship

improves in the peneplain (7-5) where the R2 is 44% and 72% respectively. There is an increase

in the saturated hydraulic conductivity as moisture of the soil is reduced since water fills the pore

spaces in the soil. Soils with light texture (Arenosols) had higher hydraulic conductivity values

than those with heavy texture (Vertisols).

There is a positive relationship between infiltration rate and hydraulic conductivity with R2 of

23% across the area (fig 7-3) but higher in peneplain 40% (fig 7-5) which is significant (99%).

This implies that the more the water enters the soil the faster it is drawn to the lower horizons of

the soil profile. Since the R2 is explaining less of the relationship, it shows that there are other

factors that influence these two variables like texture, crust, organic matter content, porosity,


70

compaction and structure as already mentioned in the first paragraph. The Arenosols showed

highest values of both hydraulic properties amongst the soil types.

7.2 Soil moisture map

In this section, the soil maps are shown that are resulting from geostatistical approach at

depth of 10cm and another at depth of 30cm. The operation assumed the Continuous

model of spatial variation (CMSV) that soil forming factors vary continuously in space

and that there is spatial dependency between them, therefore the soil properties also are

spatially variable. (See fig 7-7 and 7-8)

The results show the soil moisture distribution at depth of 10cm (fig 7-7) whilst the one

below shows distribution of soil moisture at depth of 30cm (fig 7-8). The highest values

fall in Pellic Vertisols, Calcic Luvisols and Vertic Cambisols for the depth of 10cm but at

30cm depth the highest values fall in the Vertic Cambisols and Pellic vertisols only.


71

Fig 7- 7 Soil moisture distribution map at 10cm depth

Fig 7- 8 Soil moisture distribution map at 30cm depth

7.3 Spatial variability

Although the sample size (56 points) was not adequate to reliably estimate a variogram,

we attempted it nonetheless. Results should be considered indicative rather than

definitive. This aimed at assessing the variability of soils in the area. Using soil moisture


72

as one of the hydraulic properties, ordinary kriging was performed using lag distance of

2000m for both depths with maximum point pairs of 16. The Continuous model of spatial

Variation (McBratney and Gruijter, 1992) was assumed. Fig 7-9 shows the moulded

variogram for the parameters.

The moulded variograms show that there is long-range dependence in the soil moisture at

both depths. The range is the same (4000m) but differ in the sill and nugget (2 and 32.5

for AMC at 10cm and 2 and 20 for AMC at 30cm). After 4000m, which is a point of

Fig 7- 9 Moulded variogram parameters for AMC at 10 and 30 cm depths

AMC at 10cmNugget 3Sill 32.5Range 4000

AMC at 30cmNugget 2Sill 20Range 4000


73

inflection, thereafter, the points are no longer related. Fig 7-10 to 7-13 show the maps

using ordinary kriging with their error maps.

Fig 7- 10 Soil moisture at 10cm depth (ordinary kriging

Fig 7- 11 The error map at 10cm depth


74

The Error maps show the deviation of the estimated values from the actual values that

were calculated in the field. The further you go away from the point the greater the error.

The lower values indicate less deviation and the higher values indicate greater deviation

from the true value.

Fig 7- 12 Soil moisture map at 30cm depth (ordinary kriging)

Fig 7- 13 The error map for 30cm depth


75

The results show that there is spatial variability of soils. There is spatial dependency of

the variables up to a distance of 4000m. These results also show that soil moisture spatial

distribution is related to soil type. These results also agree with Kosta (1994) who came

to the same conclusion; spatial distribution of moisture is related to soil type, vegetation

type, relative height, slope and distance from water streams.

7.3 Water-limited production potential PS2

The results from production potential situation PS2 have been tabulated in table 7-18 and 7-19 for

LUT1 and LUT2 with the growing cycle starting from Julian day 306 and ending on Julian day

61.

Table 7- 18 The water limited yield of LUT1 for cropping year 1999/2000

Mapping units Growing cycle Storage yield (SSO) Total dry matter

Pe111 306-61 6072 11691

Pe112 & Pe113 306-61 5754 9537

Pe115 306-61 1606 6485

Note: These yields are for initial matric suction (PSIint also symbolised by ΨΨΨΨ) at 500cm.

Table 7- 19 water limited yield of LUT2 in the cropping year 1999/2000

Mapping units Growing cycle Storage yield (SSO) Total dry matter (TDM)

Pe111 306-61 1234 10611

Pe112 &Pe113 306-61 1544 9352

Pe115 306-61 1206 13964

In order to evaluate the relationship of available moisture and yield, different levels of initial

matric suction were applied and table 7-20 and 7-21present the results for both LUTs.


76

Table 7- 20 LUT1 yield with different levels of PSIint

LUT1 LUT2

Mapping units PSIint levels (cm) Yield kg/ha PSIint levels (cm) Yield kg/ha 500 6072 500 1420

1000 5069 1000 1234 1500 4957 1500 1174 2000 4421 2000 1157 2500 4494 2500 1018

Pe111 3000 4327 3000 1013 500 5754 500 1268

1000 5768 1000 1544 1500 5814 1500 2069 2000 5719 2000 1951 2500 5823 2500 2039

Pe112 &Pe113 3000 5823 3000 2072 500 1606 500 1155

1000 1476 1000 1097 1500 1488 1500 1090 2000 1456 2000 1073 2500 1365 2500 1056

Pe115 3000 1338 3000 1051 Analysis of variance was calculated to compare the differences in the yield between the

PSIint. See tables 7-22 and 7-23

Table 7- 21 ANOVA for water-limited yield of LUT1

ANOVA Source of Variation SS df MS F P-value

Between Groups

62425452 2 31212726 252.6198 0

Within Groups

1853342 15 123556.1

Total

64278794 17 The ANOVA for yield of LUT1 shows that there is significant difference in yield (95%

level) at different levels of matric suction within the land units as well as between the

land units. That is successive increase in matric suction results in significant difference in


77

yield. Comparing between mapping units, it also shows that the yields are significantly

different (95)% level.

Table 7- 22 ANOVA for water-limited yield of LUT2

ANOVA Source of Variation SS df MS F P-value

Between Groups

1956145 2 978072.4 21.16624 0.000

Within Groups

693136.2 15 46209.08

Total

2649281 17 In sorghum the results also indicate that there is significant difference in the yield at 95 % level as

the matric suction is increased. The striking thing in sorghum is that in land unit Pe112 and Pe113

yield increases with increase in matric suction up to 1500 where it drops then picks up again at

2500 up to 3000. This can be attributed to the soil physical characteristics of clayloam in that land

unit.

Table 7- 23 The crop water functions at PSIint 500 and 2000cm for LUT1

PSIint at 500cm PSIint at 2000cm Day LAI Cfwater Day LAI Cfwater 306 0 1 306 0 1 316 0.01 1 316 0.01 1 326 0.07 1 326 0.07 1 336 0.29 1 336 0.29 1 346 1.06 1 346 1.06 1 356 2.53 1 356 2.53 1

1 3.81 1 1 3.81 0.89 11 3.59 0.59 11 3.56 0.3 21 2.7 0.13 21 2.63 0.11 31 1.25 0.22 31 0.46 0.22 41 0 0 41 0 0 51 0 0 51 0 0 53 0 0 53 0


78

Table 7- 24 The crop water functions at PSIint 500 and 2000cm for LUT2

PSIint at 500cm PSIint at 2000cm Day LAI Cfwater Day LAI Cfwater 306 0 1 306 0 1 316 0.02 1 316 0.02 1 326 0.15 1 326 0.15 1 336 1.2 0.92 336 1.2 0.83 346 5.27 0.51 346 4.72 0.5 356 6.27 0.45 356 5.79 0.46

1 5.91 0.47 1 5.57 0.49 11 4.44 0.71 11 4.21 0.73 21 0.47 0.4 21 0.65 0.8 31 0 0 31 0 0 41 0 0 41 0 0 50 0 0 50 0 0

In LUT1, with initial matric suction of 500,1000 and 1500cm, the water stress develops at 70th

day after planting (table 7-23) with crop water factor of 0.59 and keeps on reducing to 0.11 but it

improves again on 90th day. At this period in the growing cycle of maize, this is the flowering and

ripening stage which requires enough water to produce yield (Doorenbos and Kassam, 1979).

This implies a reduction in the yield, as the activity is not carried out accordingly. Yield reduction

is in the range of 49 to 53%.

However, as initial matric suction increases from 1500 to 3000cm, the water stress develops even

earlier at 60th day (table 7-23) with crop water factor of 0.89 which means from late vegetative

growth, flowering and yield formation are affected which eventually reduces the number of grains

on the cob as well as the weight. This event coupled with poor ripening of grains leads even to

high yield reduction (57%). The differences in yield from different land units are probably due to

soil inherent properties.

In sorghum, the story is slightly different in the sense that water stress develops quite early at 30th

day of planting (table 7-24) but this improves from 70th up to 90th day. This implies that flowering

is taking place under moisture stress but ripening coincides with improvement of moisture. Yield

reduction in sorghum is in the range of 83.5 to 90%.

The yield results were regressed with the level of initial matric suction (PSIint) applied and fig 7-

14 and 7-15 show the relationship of yield and PSIint applied.


79

Fig 7-12 Yield response for maize at different initial matric suction

The yield response to levels of matric suction applied shows that there is a positive relationship

between the moisture available in the soil and the crop yield. The R2 is good ranging from 83 to

91% (fig 7-14) which means that moisture availability, explains more of this relationship and the

remainder is explained by other factors which were not dealt with in this research but make a

contribution to the growth and development of the crop.

Fig 7- 14 Yield response to PSIint applied for LUT1

Yield response for Pe111y = -0.5858x + 5890.6

R2 = 0.835

02000400060008000

0 1000 2000 3000 4000

PSIint (cm)

Yie

ld k

g/ha

Yield response Pe112 &113y = -0.0442x + 5860.8

R2 = 0.9157

5700

5750

5800

5850

0 1000 2000 3000 4000

PSIint (cm)Y

ield

kg/

ha

Yield response Pe115y = -0.0974x + 1625.3

R2 = 0.9004

0

500

1000

1500

2000

0 1000 2000 3000 4000

PSIint (cm)

Yie

ld k

g/ha


80

Similarly, the yield response to levels of matric suction applied shows that there is a positive

relationship between the moisture available in the soil and the crop yield. The R2 is also good

ranging from 72 to 91% (fig 7-15) which means that moisture availability, explains more of this

relationship and the remainder is explained by other factors which were not dealt with in this

research but make a contribution to the growth and development of the crop.

The yield can be interpolated from the regressed graphs (fig 7-14 and 7-15). However, taking into

account of the problem faced in the data input (section 4.2.4(B)) to running of this model, one

cannot comfortably claim that these results are reliable to be used in the estimation of yield as

explained. In this case, potential yield are greater than experimental yields from the study area.

Fig 7- 15 Yield response to PSIint applied for LUT2

Yield responsePe111y = -0.1543x + 1439.3

R2 = 0.9093

0

500

1000

1500

0 1000 2000 3000 4000

PSIint (cm)

Yie

ld k

g/ha

Yield response Pe112 &113y = 0.3078x + 1285.1R2 = 0.7255

0500

1000150020002500

0 1000 2000 3000 4000

PSIint (cm)

Yie

ld k

g/ha

Yield response Pe115y = -0.0377x + 1153

R2 = 0.866

0

500

1000

1500

0 1000 2000 3000 4000

PSIint (cm)

Yie

ld k

g/ha


81

Nonhebel (1994) Nonhebel came into a conclusion that the averaged data input overestimated the

yields in Netherlands.

7.4 Physical Land Evaluation

The suitability class orders followed the ones published by FAO (1976) (see table below).

Order Suitability class S1 Highly suitable S2 Moderately suitable S3 Marginally suitable N Not suitable

The suitability in general shows that there are differences in ratings of the mapping units

depending on the requirements of the LUTs. One mapping unit is rated moderately suitable, three

are marginally suitable and five are not suitable for maize production whilst three are marginally

suitable and six are not suitable for sorghum. The ratings of individual mapping units are

discussed below. (See fig 7-13 and 7-14 for suitability maps)

Hi111 (Slope facet complex)

The mapping unit is rated unsuitable for both LUTs (sorghum and maize). The physical

suitability subclass is 4Erhz. This map unit is a scarp with slope of >16% and coupled with fine

sand renders it to highly susceptible to erosion. This map unit is not used for arable cropping.

Hi112 (Talus-hillock complex) This map unit is rated marginally suitable and not suitable for sorghum. The unit has two

different ratings because it is an association of two different soils occurring in the same mapping

unit. The physical suitability subclass is 3Erhz and 4Moav. This map unit is hilly with slope of

10% with shallow soil depth of 50-120cm. In case of maize, the unit is rated marginally suitable

with maximum limiting factors as erosion and moisture availability (3Erhz/Moav). Although the

area gets rainfall within the range of 400-600mm per year, the soil depth is shallow. This coupled

with erosion means that much of this water does not infiltrate into the soil but rather go as runoff.


82

Pe111 (Tread/Riser of the higher terrace)

The map unit is rated marginally suitable and moderately suitable for sorghum. The physical

suitability subclass is 3Erhz &2Moav/Oxav/Rtco/se/Sowo.This map unit is a compound unit.

One of the components has a slope of 10% and erosion is high. In other components, the soil is

clayloam with shallow depth (60cm) impeding root proliferation. Besides that, it contains some

gravel throughout the soil profile of the 60cm. Germination of seeds is affected by sealing as

reported by farmers during interviews.

As for maize, it is rated moderately suitable with maximum limiting factors of 2Erhz /Rtco/Sowo

for one component, 2Oxav/Rtco for the second and 3Rtco for the third component. This implies

that the third component has rooting depth as a maximum limiting factor.

Pe112 (Tread/Riser of the middle terrace)

This has been rated marginally suitable and not suitable for sorghum. The physical suitability

subclass is 4Moav and 3Erhz for both components, which constitute Pe112. Field interviews

revealed that even though farmers grow sorghum on this unit, the yields are very low.

In case of maize, it is rated not suitable and marginally suitable due to oxygen availability as

maximum limiting factor (4Oxav) meaning that the soils are poorly drained and also rated

moderately suitable due to erosion as a limiting factor (3Erhz). This implies that there are

problems of oxygen availability and erosion.

Pe113 Tread/Riser in the lower terrace

This map unit is rated not suitable for sorghum. The maximum limiting factor is oxygen

availability (4Oxav). A particle size distribution analysis result indicates 51% clay and is poorly

to imperfectly drain. For maize, it is marginally suitable (3Oxav). During interviews with farmers

from this unit, it was learnt that if it rained heavily, the soils get waterlogged for almost two

weeks. This is an indication of poor drainage.

Pe114 Tread/Riser of the Eroded terrace

The map unit is rated as marginally suitable for sorghum but marginally for maize. The maximum

limiting factor is 2Erhz whilst 3Erhz for maize. The map unit is characterised with runoff as the

area is undulating to rolling. From field observations, the area has some surface stones. It is used

for settlement.


83

Pe115 Slope floor complex of the Vale It is rated marginally suitable for sorghum and not suitable for maize. This rating coincides with

results from PS-2 where the lowest yields are from this unit for both LUTs. The physical

suitability subclass indicates maximum limiting factors of 3Oxav for sorghum and 4Oxav for

maize. This implies that the land unit has poor drainage that renders oxygen unavailable hence the

crops cannot assimilate CO2. This is supported by infiltration results of 6cm/hr for the area

(appendix A).

Pe116 Inselberg

The map unit is rated unsuitable for both LUTs (4Rtco). The physical suitability subclass

indicates rooting conditions being the maximum limiting factor. Since this are has shallow soil

effective depth (30cm) coupled with slope of 9-16%, such soils cannot support crop growth as

root proliferation is hindered.

Pu111 Summit

The map unit is rated not suitable for both LUTs. Pu111 is a compound unit with association of

three components. The first component that contributes 5% of the map unit is not suitable with

maximum limiting factor of moisture availability (4Moav). It has medium to fine sands that are

excessively drained. This implies that it cannot support growth of these crops. This map unit is

used for livestock grazing.

Table 7- 25 Physical suitability for LUT1 and LUT2

Land Mapping units

Physical Suitability subclass

Suitability class LUT1

Physical Suitability subclass

Suitability class LUT2

Hi111 4Erhz S4 4Erhz n Hi112 3Erhz & 4Moav s3 3Erhz/Moa S3&n Pe111 2Erhz/Rtco/Sowo

&2Oxav/Rtco/Sowo&2Rtco s2 3Erhz&2Moav/Oxav/Rtco/Se/

Sowo & 2Moav/Rtco s3&s2

Pe112 4Oxav & 3Erhz n &s3 4Oxav S4&s3 Pe113 2Oxav s3 4Oxav n Pe114 3Erhz s3 3Erhz S3 Pe115 4Oxav n 4Oxav n Pe116 4Rtco n 4Rtco n Pu111 4Moav n 4Moav n

Note:

Erhz is Erosion hazard Oxav is oxygen availability Sowo is soil workability

Rtco is rooting condition Se is sealing Moav is moisture availability


84

Fig 7- 16 Physical land suitability for LUT1

Fig 7- 17 Physical land suitability for LUT2


85

Summary

There is relationship between the hydraulic properties and the nature of relationship is in

two ways as observed across the area (7-3), landscapes (7-4) and soil type (7-5). Actual

moisture content exhibits negative relationship with infiltration and hydraulic

conductivity based on the overall area and landscapes but has a positive relationship on

the basis of soil type. Infiltration rate has a positive relationship with hydraulic

conductivity in all scenarios. The infiltration rate, hydraulic conductivity and texture

affect the soil moisture availability in the soil.

There is spatial dependence of soils in the area and the soils are spatially variable. The

spatial variability of soils affects soil moisture distribution as these soils have different

properties.

The water-limited production potential has revealed that increase in initial matric suction

(PSIint) leads to yield reduction implying that reduction in soil moisture especially at

reproductive stage leads to decline in yield.

The major factors leading to low yield realised by farmers (chapter6.2) in the area are

poor farm management (revealed from interviews) and low erratic rainfall.

The land evaluation ratings show that soils of hilland and plateau are not suitable for the

land utilisation types currently practised in the area mainly due to poor moisture

availability.


86

Chapter 8: Conclusion and recommendations

The findings emanating from this research are presented in this chapter on the basis of the objectives and research questions. There is a positive relationship between soil moisture availability and yield as observed from PS-

2 that as the moisture in the soil decreases the yield also decline due to moisture stress hence low

yield. The best initial matric suction (PSIint) to be applied is 500cm.

The area has three major landscapes namely Plateau, Hilland and Peneplain (corresponding with

Sandveld, escarpment and Hardveld units of FAO soil map). There are different geomorphic units

that have different soil types. The geopedological units affect the land utilisation types apart from

the precipitation received in the area. The main soils in the area are Ferralic Arenosols (mainly in

the plateau), Calcic Luvisols, Pellic Vertisols, Eutric Nitosols (mainly in peneplain), and

Endoleptic Regosols (mainly in hilland).

There is a relationship between the hydraulic properties. There is a negative relationship between

soil moisture and infiltration rate (see fig 7-3 and 7-4), a negative relationship between soil

moisture and hydraulic conductivity (see fig 7-3 and 7-4) and positive relationship between

infiltration rate and hydraulic conductivity (see fig 7-3 and 7-4). The relationship of these

hydraulic properties based on soil types is also positive (see fig 7-5).

High hydraulic conductivity and infiltration rates in sandy soils is an indication that water goes

deep into the soil profiles, and the water table is very deep. This probably feeds the ground water.

There is a wide variation for rate of evapotranspiration (0.2 to 10mm –d) that could have an

influence for the precipitation in the area and indirectly affect the ground water recharge.

There is a spatial dependency of soils in the area. This spatial variability influences soil moisture

distribution since different soils have different properties.

Soil moisture is influenced by infiltration rate, texture of soil, depth of soil profile, organic matter

content and hydraulic conductivity. Soil moisture can be used to infer the land quality moisture

availability in the land suitability evaluation process.


87

The distribution of farmlands is mostly on clay loam and sandy clay loam soils as these have a

higher capacity of holding soil moisture.

The land utilisation types considered are traditionally managed rainfed maize and sorghum grown

in single cropping system within the growing cycle of November to May.

Land evaluation reveals that soils in the hilland and plateau are not suitable for the land utilisation

types currently practised in the area. As regards the rainfall pattern in the area, these suitability

classes can be used in the planning of land use. Interviews with farmers revealed that for the past

six years, rainfall distribution has been very poor; sometimes drought develops when the crops

are approaching flowering stage and never came back. This in most cases leads to zero yield.

From these results, maize and sorghum are not suitable for the area, especially at the level of

management practised by farmers.

Recommendations

For further studies, it is recommended to do soil moisture measurements during rainy

season for the following reasons:

• Time sequence monitoring of soil moisture over entire season to identify critical

periods and assess detailed performance of PS123.

• Since hydraulic conductivity is a highly variable soil property, a single measured

value is unreliable indicator of hydraulic conductivity of soil; therefore more

measurements should be conducted to come up with a reliable estimate.

• To enhance understanding of the behaviour of soil hydraulic properties in the

area.

Improvements in terms of cultural practices is needed like early land preparation and

weeding at the right time. Application of fertilizer especially of organic type should be

encouraged since this improves soil structure, nutrient status and water holding capacity.


88

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Timmermans, W.J., and A.M.J. Meijerink. 1999. Remotely sensed actual evapotranspiration: implications for groundwater management in Botswana 1:222-234.

F. J. Leji (ed.) 1997. Riverside International Workshop on Soil Hydraulic Properties, Riverside, California. USDA.

USDA. 1998. Soil quality indicators: Infiltration [Online]. Available by National Soil Survey centre in coopertaion with soil Quality Institute http://soils.usda.gov/sqi/files/Infiltration.pdf (verified 08/01/03).

Van Keulen, H., and J. Wolf. 1986. Modelling of agricultural production: weather, soils and crops Centre for Agricultural Publishing and Documentation, Wageningen.


90

Voortman, R., (ed.) 1985. Guidelines for rainfed agriculture in Mozambique. FAO, Rome. Ward, R.C., and M. Robinson. 1989. Principles of hydrology. 3rd edition ed. McGraw-Hill Book

Company Europe, Berkshire, England. Wellfield Consulting Services. 1998. Serowe wellfield 2 extension project (TB10/3/10/95-96,

Main report. Department of Water Affairs, Gaborone, Botswana. Wilding, L.P., and L.R. Drees. 1983. Spatial variability and pedology. Pedogenesis and soil

Taxonomy: 83-116. Wokabi, S.M. 1994. Quantified Land Evaluation for maize Yield GAP Analysis at three sites on

the Eastern slope of Mount Kenya. Unpublished Ph.D thesis, University of Ghent, Gent. Zinck, J.A. 1988/89. Physiography and soils, pp. 156 ITC Lecture notes: SOL.41, Enschede,

Netherlands.


91

Appendix A: Soil Hydraulic properties results

Site X_ coord Y_coord Infilt.rate Moist. at 10cm

Moist.at 30cm K cm/day

EPT 001 474663 7539777 18 4.03 2.38 347.10

EPT 002 475335 7531980 24 7.45 4.26 248.40

EPT 003 475066 7535877 27 4.85 1.19 198.10

EPT 004 475135 7530185 28.2 4.72 1.46 99.40

ESC 007 473503 7534453 24.5 5.28 0.22 99.40

ESC 027 475317 7531820 12 5.67 2.69 29.80

ESC 051 474197 7529534 26.5 7.91 1.41 149.00

Hard 001 460758 7522868 18 9.66 12.81 29.80

HPT 001 466980 7513874 20.5 1.36 1.69 149.00

HPT 002 466771 7510453 6.1 6.35 9.17 9.9

HPT 003 465347 7507938 20 1.91 0.93 99.4

HPT 004 468575 7513048 12 6.24 8.76 9.9

HPT 005 469774 7518089 6 6.88 9.09 9.9

HPT 006 467215 7517154 6 8.24 7.21 9.9

HPT 007 467604 7519059 18 4.86 8.24 49.7

HPT 008 468601 7518513 17.8 4.58 5.81 99.4

SVD 001 435542 7525186 47.5 0.38 0.44 397.4

SVD 010 434542 7525186 41.3 1.31 2.54 496.8

SVD 200 436542 7527186 27.5 0.77 0.87 447.1

SPT 001 433495 7527033 22.5 0.75 0.83 149

SPT 002 428575 7531451 24.5 1.60 2.12 248.4

SPT 003 444677 7516908 35.2 1.97 1.13 397.4

SPT 004 460780 7525102 18 4.04 1.08 248

Hard 36 466077 7515673 14 1.56 2.60 794.9

Hard 13 466910 7510494 17 8.38 1.67 99.4

Hard 14 475015 7530045 17.5 1.06 1.54 99.4

EST 002 476357 7534631 21.8 20.70 7.99 149

ESC 061 468225 7528791 27.6 6.21 2.14 695

ESC 062 468349 7528318 25.3 6.03 2.82 149

PLT 011 471741 7531685 22.3 20.92 11.84 298.1

PLT 019 470620 7532142 24.5 2.94 5.79 99.4

PLT 024 470047 7532187 21.8 5.06 6.65 397.4

PLN 028 471611 7532947 17.5 15.71 12.90 198.7

PLT 053 471592 7533175 12.5 7.62 6.62 248.4

EPT 021 474564 7539239 18 1.12 1.41 99.4

EPT 012 473645 7539268 18.5 1.12 1.30 844.6

FRM 001 460594 7520848 14.5 3.45 5.11 198.7

FRM 002 463636 7519154 8 9.60 12.07 24.8

FRM 003 464878 7519907 7.3 9.16 11.64 9.9


92

FRM 004 463525 7519876 12.5 9.41 10.11 9.9

FRM 005 481118 7537905 8.2 7.49 9.40 9.9

FRM 006 485189 7539910 8.5 6.77 8.99 9.9

FRM 007 484385 7538250 14.3 7.51 11.04 347.8

SVD 081 462000 7527775 36.2 2.40 1.19 397.4

SVD 082 470521 7535305 25.5 0.72 4.63 99.4

SVD 083 464693 7539551 28.3 5.69 1.73 397.4

FRM 008 484223 7538215 8.5 3.19 2.51 9.9

FRM 009 463159 7517322 8.5 10.96 12.22 9.9

ESC 063 471611 7532947 8.3 18.60 12.76 9.9

FRM 010 463153 7517319 8.8 7.15 10.59 447.1

FRM 011 466658 7510188 6 6.30 8.11 9.9

FRM 012 466643 7510139 6 4.01 8.83 9.9

PLN 001 481157 7537855 16.5 1.47 0.69 347.8

Hard 059 461653 7523416 18.8 7.09 13.56 99.4

Hard 071 474783 7530344 15.5 1.39 2.03 99.4

Hard 085 475396 7528069 17.8 1.22 1.70 99.4

EST 003 476642 7535642 18 2.00 2.76 99.4


93

Appendix B: Soil profile description

Appendix 1: Soil Profile Description Soil profile SPT 001/2002 A. Information on soil profile site

Date of examination 25/09/02

Type of observation mini pit

Authors Ermias Aynekulu, Esther Mweso.

Location 433495, 7527033,

Altitude 1213 m.a.s.l.

Geopedological unit Pu111

Topography flat

Slope 0-2% Parent material Aeolian sand Vegetation open savannah shrub

land with good grass cover

Land use open grazing

B. General information on the soil profile Classification (WRB) Haplic Arenosol Human influence vegetation moderately

disturbed Effective soil depth very deep, >150cm

Drainage class excessively drained

Internal drainage well drained

External drainage neither receiving nor

shedding

Ground water depth very deep, >150cm

Surface stoniness none

Rock outcrops none Evidence of erosion none

C. Soil profile description

Horizon Depth (cm) Description A

0-10

Yellow brown (10YR 5/4) when dry and dark yellowish brown (10YR 4/6) when moist; fine sand; massive structure; medium sub angular blocky; loose when dry and very friable when moist; non sticky and non plastic; fine to medium size roots are common; field pH 4.5; gradual boundary

C1

10-40

Very brownish yellow (10YR 6/8) when dry and yellow brown (10YR 5/4) when moist; fine sand; massive structure; loose when dry and very friable when moist; non sticky and non plastic; few medium roots; field pH 5.0; gradual boundary

C2

40-70

Yellowish brown (10YR 5/8)when dry and when moist; fine sand; massive structure; loose when dry and very friable when moist; non sticky and non plastic; few fine roots; field pH 5.5; gradual boundary

C3

70-120

Very brownish yellow (10YR 6/8) when dry and yellowish brown (10YR 5/6) when moist; fine sand; weak massive structure; loose when dry and very friable when moist; non-sticky and non-plastic; few fine roots; field pH 5.5.


94

Soil profile SPT 002/2002 A. Information on soil profile site

Date of examination 25/09/02

Type of observation mini pit Authors Ermias Aynekulu,

Esther Mweso. Location 428575,7531451


Geopedological unit Pu111 (Kalahari sand)

Topography flat

Slope 0-2% Parent material Aeolian sand Vegetation Savannah Land use open grazing

B. General information on the soil profile Classification (WRB) Epidystric Arenosol Human influence vegetation moderately

disturbed Effective soil depth very deep, >150cm




shedding



Rock outcrops none

Evidence of erosion none Sealing /crusting none

Moisture condition dry


Horizon Depth (cm) Description Ah

0-15

Very brown (10YR 4/3) when dry and yellowish brown (10YR 5/4)) when moist; loamy very fine sand; massive structure; slightly hard when dry and loose when wet; non sticky and non plastic; many very fine, many fine pores; fine and medium roots are common; field pH 5; gradual boundary

C1

15-35

Dark yellowish brown (10YR 3/4) when dry and dark greyish brown (10YR 4/2) when moist; loamy very fine sand; weak massive structure; soft when dry and loose when wet; non sticky and non plastic; many fine pores; medium size roots are common; field pH 6.5; gradual boundary

C2

35-80

Very dark yellowish brown (10YR4/4) when dry and dark greyish brown (10YR4/2) when moist; loamy very fine sand; weak massive structure, medium to coarse sub-angular blocky; loose when dry and wet ; non sticky and non plastic; many fine pores; few coarse roots; field pH 7; gradual boundary

C3

80-140

Very yellowish brown (10YR 5/6) when dry and brown (10YR 4/3) when moist; loamy very fine sand; weak massive structure; loose when dry and wet; non sticky and non plastic; many fine pores; few coarse roots; field pH 7.0


95

Soil profile SPT 003/2002 A. Information on soil profile site Date of examination 26/09/02


Location 444677, 7516908 Altitude 1200 m.a.s.l.


Topography flat

Parent material sand

Slope 0-2% Parent material Aeolian sand

Vegetation savannah Land use open grazing

B. General information on the soil profile Classification (WRB) Hypoluvic Dystric

Arenosol Human influence vegetation disturbed Effective soil depth very deep, >150cm




shedding



Rock outcrops none

Evidence of erosion wind

Sealing /crusting none




0-10

Dark greyish brown (7.5YR 4/4) when moist; fine sand; loose when dry and wet; non stick non plastic; many very fine pores, fine and medium roots are common; field pH 6.0

Bt1

10-30

Olive brown (5YR 4.5/4) when moist, loamy fine sand; slightly hard when dry and loos when wet: non sticky and non plastic; clay bridges; many very fine pores; few medium size roots; field pH 6.5

Bt2

30-120

Light olive brown (5YR5/4) when moist, loamy fine sand; slightly hard when dry and loos when wet: non sticky and non plastic; clay bridges; many fine pores; few medium size roots; field pH 6.5


96

Soil profile SPT 004/2002 A. Information on soil profile site Date of examination 24/09/02



Location 435542,7525186,



Topography flat

Slope 0-2% Parent material sandstone Vegetation Savannah woodland

Land use Grazing

B. General information on the soil profile Classification (WRB) Hypoluvic Dystric

Arenosol Human influence vegetation disturbed Effective soil depth very deep, >150cm




shedding



Rock outcrops none

Evidence of erosion wind





0-15

Very dark grey (10YR 6/2.5) when dry dark brown (10YR 4/2.5) when moist; fine sand; weak massive structure; loose when dry and friable when moist; non sticky and non plastic; fine roots are common; field pH 5; gradual boundary

C1

15-45

Very dark grey (10YR 6/8) when dry and dark brown (7.5YR 5/5) when moist; Gradual boundary, fine sand; weak massive structure; loose when dry and very friable when moist; non sticky and non plastic; medium size roots are common; field pH 5.5; gradual boundary

C2

45-130

Very dark grey (10YR 6/3.5) when dry and dark brown (7.5YR 5/4) when moist; fine sand; weak massive structure; loose when dry and very friable when moist; non sticky and non plastic; few fine; field pH 6


97

Soil profile EPT 001/2002 A. Information on soil profile site Date of examination 13/09/02 Type of observation mini pit Authors Ermias Aynekulu,

Esther Mweso. Location 474663, 7539777 (300

m from the main road to Khama Rhino sanctuary)

Altitude 1294m.a.s.l. Geopedological unit Hi111 Topography flat

Slope 0-2 % Parent material Aeolian sand Vegetation Savannah woodland Land use open grazing

B. General information on the soil profile Classification (WRB) Ferralic Arenosol Human influence vegetation slightly

disturbed Effective soil depth Very deep, >150cm

Drainage class somewhat excessively drained

Internal drainage never saturated (well drained)

External drainage neither receiving nor shedding

Ground water depth very deep, >150cm Surface stones none Rock outcrops none Evidence of erosion none Sealing /crusting none


C. Soil profile description Horizon Depth (cm) Description A

0-18

Reddish brown (5YR4/4) when dry and yellowish red (5YR4/6) when moist; fine sand; weak with massive structure; soft when dry and very friable when moist; non sticky and non plastic; few coarser roots; field pH4.5, smooth boundary

C

18 +

Reddish yellow (7.5YR 6/8)when dry and strong brown (7.5YR5/8) when moist; fine sand; weak with massive structure; slightly hard when dry, very friable when moist; non sticky and non plastic; fine roots are common, field pH 5.0 smooth boundary


98

Soil profile EPT 002/2002 A. Information on soil profile site Date of examination 15/09/02 Authors Ermias Aynekulu,

Esther Mweso. Location 475335, 7531980 (100m

from the military camp fence

Altitude 1050m.a.s.l. Geopedological unit Hi112 Topography: flat Slope 0-2% Parent material Aeolian sand Vegetation savannah woodland Land use open grazing

B. General information on the soil profile Classification (WRB) Arenosol Human influence Slight vegetation

disturbance Effective soil depth very deep, >150cm Drainage class well drained Internal drainage rarely saturated External drainage slow run-off

Ground water depth very deep, >150cm Surface stones none Rock outcrops none Evidence of erosion water, 0-5% area

affected Sealing /crusting none

Moisture condition moist



0-16

Dark greyish brown (2.5Y4/2) when dry and light olive brown (2.5 Y 5/3) when moist; fine sand; weak with massive structure; soft when dry and loose when moist; slightly sticky and non- plastic; very fine pores are common; very few fine roots; field pH5.5 abrupt

B

16+

Reddish yellow (7.5YR 6/8) when dry and strong brown (7.5YR 5/8) when moist; fine sand; weak massive structure; hard when dry and very friable when moist; non sticky non plastic; few fine roots; pH 5


99

Soil profile EPT 003/2002 A. Information on soil profile site Date of examination 18/09/02 Authors Ermias Aynekulu,

Esther Mweso. Location 475066, 7535877, 6Km

west of Paje village Altitude 1211m.a.s.l.

Geopedological unit Hi112 foot of the

escarpment

Topography flat

Slope 0-2% Parent material sandstone Vegetation savannah woodland


B. General information on the soil profile Classification (WRB) Arenic Acrisol Human influence slight vegetation

disturbance Effective soil depth Very deep, >150cm Drainage class somehow excessively

drained Internal drainage none External drainage neither receiving nor

shedding

Ground water depth Very deep, >150cm Surface stones none Rock outcrops none Evidence of erosion vegetation disturbance Sealing /crusting none

Moisture condition first 20cm moist, the

rest is dry



0-15

Reddish brown (7.5YR7/6) when dry and strong brown (7.5YR4/6) when moist; loamy fine sand;

massive structure; loose when dry and moist; non sticky and non plastic; fine pores are common;

very fine roots are common; field pH5; clear boundary

Bt1

15-35

Reddish yellow (7.5YR6/6) when dry and (7.5YR6/4) when moist; loamy fine sand; massive

structure; loose and friable when moist; non sticky and non plastic; fine pores are common; few

medium size roots; field pH5.7; gradual boundary Bt2

35-54

Pink (7.5YR8/4) when dry and strong brown (7.5YR5/6) when moist; loamy fine sand; massive

structure; soft when dry and friable when moist; non-sticky and non-plastic; very few mottles of

medium size. Common clay cutans ; very fine pores are common; very few fine roots; field

pH5.7; clear boundary BC

54-60


structure; soft when dry and friable when moist; non sticky and non plastic; Abundant coarse,

angular, weathered sandstone rock fragments Fine pores; many mottles of medium size grey in

colour. Common clay cutans ; very fine pores are common; few fine roots; field pH5.5; clear

boundary BC2

60-120


structure; slightly hard when dry and friable when moist; non-sticky and non plastic; Dominant

stones, angular, weathered sandstone rock fragments Fine pores; many mottles of medium size

grey in colour. Common clay cutans; many very fine pores; few fine roots; filed pH 5.0


100

Soil profile HPT 001/2002 A. Information on soil profile site Date of examination 20/09/02 Type of observation mini pit


Location 465347, 7507938 Altitude 1025 m.a.s.l.

Geopedological unit Sd111

Topography flat

Slope 0-2% Parent material alluvial material Vegetation Savannah bush


B. General information on the soil profile Classification (WRB) Arenic Rhodic Acrisol Human influence slight vegetation

disturbance Effective soil depth Very deep, >150cm

Drainage class somehow excessively

drained



shedding

Ground water depth Very deep, >150cm

Surface stones none Rock outcrops none Evidence of erosion none Sealing /crusting none




0-15

Yellowish red (5YR5/6) when dry and when moist; loamy sand; massive structure; slightly hard when dry and very friable when moist; non sticky and non plastic; bridges of sand coated but not strongly cutans; many medium pores; fine roots are common; biological activities are common; field pH 6.0; gradual boundary

Bt1

15-80

Yellowish red (5YR6/8) when dry and moist; loamy sand; massive structure; slightly hard when dry and very friable when moist; non sticky and non plastic; clay bridges and sand coated, but not strong; many medium pores; many fine roots; field pH 5.5; gradual boundary

Bt2

80-130

Yellowish red (5YR5/6) when dry and moist; loamy sand; massive structure; slightly hard when dry and very friable moist; non sticky and non plastic; clay bridges and sand coated, but not strong; many medium pores; few medium roots; field pH 5.0


101

Soil profile HPT 002/2002 A. Information on soil profile site Date of examination 20/09/02



Location 466771, 7510453,

15m from the road to

sokwe hill


Geopedologic unit Hi412

Topography Flat

Slope 0-2% Parent material Alluvial deposits Vegetation Shrub Land use open grazing

B. General information on the soil profile Classification (WRB) Arenic Rhodic

Acrisol Human influence vegetation disturbed Effective soil depth very deep, >150cm

Drainage class poorly drained

Internal drainage not known

External drainage






0-22

Dark grey (5Y4/1) when dry and very dark grey (5Y3/1) when moist; sandy clay; very strong structure is coarse and prismatic; hard when dry and very firm when moist; sticky and plastic; clear slicken sides; fine roots are common; field pH 8.0; gradual boundary

Bw1

22-70

Dark grey (5Y4/1) when dry and very dark grey (5Y3/1) when moist; sandy clay; very strong structure which is coarse and prismatic; very hard when dry and very firm when moist; very sticky and very plastic; clear slicken sides; few coarse roots; field pH 7.5; gradual boundary

Bw2

70-120

Dark grey (5Y4/1) when dry and very dark grey (5Y3/1) when moist; sandy clay; excessively hard when dry and very firm when moist; very sticky and very plastic; clear slicken sides; no roots; field pH 7.0


102

Soil profile HPT 003/2002 A. Information on soil profile site Date of examination 20/09/02 Type of observation mini pit Authors Ermias Aynekulu,

Esther Mweso. Location 466980, 7513874, near

Sokwe hill Altitude 1067m.a.s.l. Geopedological unit Hi412, sand deposit

Topography Flat

Slope 0-2% Parent material Sandstone Vegetation shrub savannah Land use open grazing

B. General information on the soil profile Classification (WRB) Arenic Rhodic Arenosol Human influence vegetation disturbed Effective soil depth very deep, >150cm



shedding





Horizon Depth (cm) Description Bt1

0-10

Red (10R4/6) when dry and dark red (10R3/6) when moist; very fine loamy sand; massive structure; loose when dry and very friable when moist; non sticky and non plastic; many prominent cutans ; field pH 5.5; clear boundary

Bt2

10-30

Red (10R4/6) when dry and dusky red (10R3/4) when moist; very fine loamy sand; massive structure; slightly hard when dry and friable when moist; non sticky and non plastic; Many prominent cutans; field pH 5.5; clear boundary

Bt3

30+

Dusky red (10R3/4)) when dry and dark red (10R3/6) when moist; very fine loamy sand; hard when dry and firm when moist; slightly hard when dry and very friable when moist; non sticky and non plastic; Many prominent cutans; field pH 5


103


Type of observation Mini-Pit


Location 468575,7513048,



Topography flat

Slope 0-2%

Parent material Alluvial deposits Vegetation Savannah grassland

with scanty shrubs

Land use Grazing

B. General information on the soil profile Classification (WRB) Vertisol Human influence vegetation disturbed

Effective soil depth Very deep, >150cm




shedding



Rock outcrops none Evidence of erosion none Sealing /crusting medium


C. Soil profile description Horizon Depth

(cm) Description

Ah

0-20

Dark grey (5Y4/1) when dry and very dark grey (5Y3.1/1) when moist; sandy clay; very strong structure which is coarse and prismatic; hard when dry and very firm when moist; sticky and plastic; clear slicken sides; fine roots are common; field pH 7.5; gradual boundary

Bt1 20-50

Dark grey (5Y4/1) when dry and moist; sandy clay; very strong structure which is coarse and prismatic; hard when dry and very firm when very sticky and very plastic; clear slicken sides; few coarse roots; field pH 8.0; gradual boundary

Bt2

50-90

Dark grey (5Y3/1) when dry and black (5y2.5/1) when moist; sandy clay; very strong structure that is coarse and prismatic; hard when dry and very firm when moist; very sticky and very plastic; clear slicken sides; no roots; field pH 7.5; gradual boundary

Bt3

90-130

Dark olive grey (5Y3/2) when dry and dark grey (5Y4/1) when moist; sandy clay; very strong structure that is coarse and prismatic; hard when dry and very firm when moist; clear slicken sides; very sticky and very plastic; no roots; field pH 7.5


104


Type of observation mini-Pit


Location 469774,7518089,


Geopedological unit Pe311

Topography flat Slope 0-2% Parent material alluvial deposit Vegetation savannah bush Land use open grazing

B. General information on the soil profile Classification (WRB) Vertisol Human influence vegetation slightly

disturbed

Effective soil depth very deep, >150cm




shedding



Rock outcrops none

Evidence of erosion none

Sealing /crusting medium



Horizon Depth (cm)

Description

Ah

0-15

Black (5Y2.5/1) when dry and moist; sandy clay; very strong structure which is coarse and prismatic; slightly hard when dry and moist; sticky and plastic; clear slicken sides; fine roots are common; field pH 7.5; gradual boundary

Bt1

15-70

Black (5Y2.5/1) when dry and dark olive grey (5Y3/2) when moist; sandy clay; very strong structure which is coarse and prismatic; sticky and plastic; clear slicken sides; fine roots are common; field pH7.0; gradual boundary

Bt2

70+

Black (5Y2.5/2) when dry and hen dry and moist; sandy clay; very strong structure which is coarse and prismatic; sticky and plastic; clear slicken sides; fine roots are common; field pH 8.5


105

Soil profile HPT 006/2002 A. Information on soil profile site Date of examination 22/09/02 Type of observation Mini-Pit Authors Ermias Aynekulu,

Esther Mweso. Location 467215, 7517154 Type of observation mini pit Altitude 1094 m.a.s.l.


Topography Flat

Slope 0-2%

Parent material Alluvial deposits Vegetation Savannah shrub Land use farmland

B. General information on the soil profile Classification (WRB) Endoleptic Vertic

Cambisol Human influence none





shedding



Rock outcrops none


Sealing /crusting very thick


Remark: A farmland closer to Sokwe hill



0-15

Very dark grey (10YR3/1) when dry and dark brown (10YR3/3) when moist; sandy clay; strong sub angular structure; extremely hard when dry and firm when moist; stick and very plastic; fine roots are common; field pH 7.5; gradual boundary

Bw1

15-40

Very dark grey (10YR3/1) when dry and very dark greyish brown (10YR3/2) when moist; sandy clay; very strong sub angular structure; extremely hard when dry and very firm when moist; stick and very plastic; few medium size roots; field pH 8.0; gradual boundary

Bw2

40-70

Very dark grey (10YR3/1) when dry and very dark greyish brown (10YR3/2) when moist; sandy clay loam; very strong sub angular structure; extremely hard when dry and very firm when moist; sticky and very plastic; field pH 8.0


106

Soil profile HPT 007/2002 A. Information on soil profile site Date of examination 22/09/02 Type of observation Mini-Pit


Location 467604, 7519059



Topography Flat

Slope 0-2% Parent material Alluvial deposits

(Andezitic substratum) Vegetation Savannah shrub

Land use Grazing

B. General information on the soil profile Classification (WRB) Endoleptic Cutanic

Luvisol Human influence none



drained

Internal drainage Rapid

External drainage slow run-off



Rock outcrops none



Moisture condition Dry


Horizon Depth (cm)

Description

Ah

0-15

Dark greyish brown (10YR3/1or 2) when dry and dark brown (10YR3/3) when moist; fine sandy loam; weak sub- angular blocky structure; slightly hard when dry and friable when moist. Slightly sticky and plastic; clay cutans are common; many fine pores; fine and medium roots are common; field pH 7.5; wavy boundary

Bt1

15-40

Very dark grey (10YR4/2) when dry and very dark greyish brown (10YR4/4) when moist; sandy clay loam; weak sub angular blocky structure; slightly hard when dry and firm when moist; slightly sticky and plastic; many fine pores; few medium and coarse roots; field pH 7.5; wavy boundary

Bt2

40-70

Very dark grey (7.5YR4/3) when dry and very dark greyish brown (7.5YR3/3) when moist; sandy clay loam; hard when dry and firm when moist; gravel sticky; fine pores are common; no roots; field pH 7.5


107


Type of observation Min-Pit Authors Ermias Aynekulu,

Esther Mweso. Location 468601, 7518513



Topography Flat

Slope 2-5% Parent material Sandstone

Vegetation Woodland

Land use Grazing

B. General information on the soil profile Classification (WRB) Endoleptic Endoeutic

Regosol Human influence vegetation disturbed

Effective soil depth 35cm


drained


External drainage slow run-off



Rock outcrops none

Evidence of erosion sheet erosion


Moisture condition Dry


Horizon Depth (cm)

Description

A

0-10

Very dark grey (5YR4/3) when dry and dark brown (5YR3/3) when moist; sandy clay loam; loose when dry and friable when moist; non sticky and non plastic; field pH 7.0; wavy boundary

Cr

10-35

Very dark grey (5YR4/3) when dry and dark brown (5YR3/3) when moist; coarse sandy loam; loose when dry and when moist; non sticky and non plastic; field pH 7.5


108

Appendix C: Climatic file

'Serowe002" -22.16, 26.4, 1040 1 30.5 20 0 0.86 0.637 7.5 0.543 41 28.1 19.2 1.52 0.81 0.635 8.6 0.53

2 30.2 20 0.6 0.76 0.638 7.5 0.544 42 24.4 18.4 2 0.95 0.634 8.6 0.529

3 26 19.4 1.4 0.85 0.64 7.6 0.545 43 27.4 19 0.4 0.91 0.633 8.6 0.528

4 27.9 19.4 0 0.88 0.641 7.6 0.547 44 27.5 20.8 0.4 0.84 0.632 8.6 0.527

5 28.2 20.5 0 0.8 0.643 7.7 0.548 45 28.5 19.8 0 0.94 0.631 8.6 0.526

6 30.5 20.1 0.9 0.8 0.645 7.7 0.549 46 29.3 21.5 5 0.91 0.63 8.7 0.524

7 29.5 21 0.4 0.8 0.646 7.8 0.55 47 28.3 19.5 1.8 0.9 0.627 8.6 0.522

8 32.5 20 0 0.7 0.648 7.8 0.552 48 25.8 17.8 0 0.81 0.623 8.6 0.519

9 27 19.5 0 0.9 0.649 7.9 0.553 49 25.5 16 0 0.56 0.74 8.6 0.516

10 27.7 19.5 0 0.85 0.651 7.9 0.554 50 27.7 17.5 0 0.91 0.616 8.5 0.513

11 29.7 19.1 0 0.79 0.652 8 0.555 51 29.7 17.2 0 0.79 0.613 8.5 0.51

12 30 18.1 0 0.73 0.654 8 0.557 52 28.5 20.4 0 0.94 0.61 8.5 0.507

13 27.5 20.1 0 0.62 0.655 8.1 0.558 53 31 18.8 0 0.83 0.606 8.4 0.504

14 25.6 18 0 0.7 0.657 8.1 0.559 54 28.5 19 0.21 0.86 0.602 8.4 0.501

15 21.3 18 0.3 7.9 0.86 8.2 0.56 55 24 17.9 5.4 0.95 0.599 8.4 0.498

16 21.5 17 6.03 0.98 0.658 8.2 0.559 56 21.8 17.5 3.72 0.95 0.595 8.3 0.496

17 22.2 15.4 1.3 0.86 0.657 8.2 0.558 57 24.8 17.5 1.4 0.97 0.592 8.3 0.493

18 20 17 0 0.87 0.656 8.2 0.557 58 26 18.6 1.4 0.92 0.588 8.3 0.49

19 23.5 16.2 0 0.81 0.655 8.2 0.556 59 25.5 19.2 0 0.82 0.585 8.2 0.487

20 24.6 14.5 0 0.8 0.654 8.3 0.555 60 26 17 0 0.86 0.582 8.2 0.484

21 26.8 13.5 0 0.8 0.653 8.3 0.554 61 28.5 17.5 0 0.95 0.578 8.2 0.481

22 28.7 13.8 0 0.7 0.652 8.3 0.552 62 28.5 18.5 0 0.91 0.574 8.1 0.478

23 28.5 14.6 0 0.7 0.651 8.3 0.551 63 29.1 19.5 0 0.82 0.571 8.1 0.475

24 28.3 17.2 0 0.55 0.65 8.3 0.55 64 29.6 18 0 0.79 0.567 8.1 0.472

25 23.5 18.8 0 0.77 0.649 8.3 0.549 65 29 18.1 0 0.8 0.564 8 0.47

26 27.4 19 2 0.94 0.649 8.3 0.548 66 27 19 0 0.91 0.56 8 0.467

27 28.1 19.5 0.8 0.95 0.648 8.4 0.547 67 27.2 18 0 0.87 0.557 8 0.464

28 31.7 18.6 0.001 0.93 0.647 8.4 0.545 68 27.2 17.7 0 0.91 0.554 7.9 0.461

29 32 16.8 0 0.51 0.646 8.4 0.544 69 30.6 17 0 0.82 0.55 7.9 0.458

30 33.2 15.3 0 0.52 0.645 8.4 0.543 70 30.3 15.6 0 0.83 0.546 7.9 0.455

31 35 17.1 0 0.64 0.644 8.4 0.542 71 27.5 18.2 0 0.76 0.543 7.8 0.452

32 32.6 20.1 0 0.76 0.643 8.4 0.541 72 27 17.4 0 0.84 0.539 7.8 0.449

33 33.8 19.5 0 0.74 0.642 8.5 0.54 73 28.6 18.8 0 0.86 0.536 7.8 0.446

34 34.9 19.8 0 0.78 0.641 8.5 0.538 74 30.1 17 0.3 0.95 0.532 7.7 0.444

35 31.1 18.3 0 0.64 0.64 8.5 0.537 75 28 17.5 0 0.83 0.529 7.7 0.441

36 31.1 18 0 0.66 0.64 8.5 0.536 76 28.2 19.4 0 0.96 0.525 7.7 0.438

37 30 18.7 11.9 0.91 0.639 8.5 0.535 77 27 18.4 0 0.94 0.522 7.7 0.435

38 23 19 2.52 0.96 0.638 8.5 0.534 78 24.5 18.5 0 0.96 0.518 7.8 0.432

39 22.5 20 2.9 0.87 0.637 8.6 0.533 79 22.4 19 1.2 0.95 0.515 7.8 0.429

40 26.4 19.1 0.7 0.96 0.636 8.6 0.531 80 26 18.5 4.1 0.95 0.511 7.8 0.426


109

81 26.5 18.5 0.6 0.91 0.508 7.8 0.423 121 21 11.1 0 0.85 0.366 8.2 0.304

82 27 17.8 5.4 0.88 0.504 7.8 0.42 122 25.2 8 0 0.84 0.362 8.2 0.301

83 27.8 16.7 0 0.87 0.501 7.8 0.417 123 27 9 0 0.75 0.359 8.2 0.298

84 29 17 0 0.89 0.497 7.8 0.414 124 23.4 11.8 0 0.81 0.355 8.2 0.295

85 30 17 0 0.82 0.494 7.8 0.412 125 24.5 13 0 0.96 0.351 8.2 0.292

86 25.5 16.2 0 0.85 0.49 7.8 0.409 126 25.2 11 2.2 0.89 0.348 8.2 0.289

87 28.2 17 0 0.91 0.487 7.8 0.406 127 24 12 0.9 0.95 0.344 8.2 0.286

88 27.5 16 0 0.9 0.483 7.8 0.403 128 23.4 6.2 0 0.83 0.341 8.2 0.283

89 25.5 15.6 0 0.85 0.48 7.8 0.4 129 22.2 9 0 0.92 0.337 8.3 0.28

90 28.2 18 0 0.89 0.476 7.9 0.397 130 23.5 7.5 0 0.82 0.334 8.3 0.277

91 27 17.5 0 0.87 0.473 7.9 0.394 131 22 10.1 0 0.91 0.33 8.3 0.274

92 23.5 19 0 0.82 0.469 7.9 0.391 132 23 7.5 0 0.84 0.326 8.3 0.271

93 27.5 14 0 0.95 0.466 7.9 0.388 133 21.5 7.3 0 0.9 0.323 8.3 0.268

94 29.5 13 0 0.94 0.462 7.9 0.385 134 18.1 10.5 0 0.83 0.319 8.3 0.265

95 21.3 13.6 0 0.79 0.459 7.9 0.383 135 21.6 3 0.04 0.83 0.322 8.3 0.261

96 23.5 13.5 0 0.9 0.455 7.9 0.38 136 22.5 3.4 0 0.81 0.313 8.3 0.26

97 23.1 14.5 0.13 0.9 0.452 7.9 0.377 137 22 4.5 0 0.78 0.311 8.3 0.258

98 24 13.7 0 0.9 0.448 7.9 0.374 138 22.5 7 0 0.94 0.309 8.3 0.256

99 27 11 0 0.9 0.445 7.9 0.371 139 24.7 5.7 0 0.8 0.307 8.3 0.254

100 25.5 11.8 0 0.84 0.441 7.9 0.368 140 24.8 6.5 0 0.73 0.304 8.3 0.252

101 25 13.4 0 0.86 0.438 7.9 0.365 141 24.3 6 0 0.77 0.302 8.3 0.25

102 27.5 13.5 0 0.9 0.434 8 0.362 142 24.2 6.6 0 0.75 0.3 8.3 0.248

103 27.8 12 0 0.86 0.431 8 0.359 143 24.8 7.09 0 0.71 0.298 8.2 0.246

104 26.6 13.5 0 0.86 0.427 8 0.356 144 25.5 5.4 0 0.72 0.295 8.2 0.244

105 22 13.4 0 0.87 0.423 8 0.354 145 24.5 5.5 0 0.69 0.293 8.2 0.242

106 22.92 16.6 0 0.97 0.42 8 0.35 146 25.4 6 0 0.7 0.291 8.2 0.24

107 24.5 10.5 0 0.98 0.416 8 0.347 147 26 10.1 0 0.68 0.289 8.2 0.238

108 25.5 11 0 0.97 0.413 8 0.344 148 24.5 3.4 0 0.68 0.287 8.2 0.236

109 26 11.5 2.3 0.86 0.409 8 0.341 149 24.4 6.41 0 0.95 0.284 8.2 0.234

110 24.1 12.7 0 0.76 0.405 8 0.338 150 24 3.6 0 0.74 0.282 8.2 0.232

111 22 13.5 0 0.85 0.402 8 0.335 151 25.7 5 0 0.62 0.28 8.2 0.231

112 24.8 15.4 0 0.91 0.398 8.1 0.332 152 23.1 5 0 0.62 0.278 8.1 0.229

113 27.5 11 0 0.91 0.395 8.1 0.329 153 22.5 2.6 0 0.87 0.275 8.1 0.227

114 30.2 13 0 0.72 0.391 8.1 0.326 154 22.6 2 0 0.73 0.273 8.1 0.225

115 31.5 13 0 0.72 0.388 8.1 0.323 155 21.2 4.1 0 0.84 0.271 8.1 0.223

116 30 11.5 0 0.68 0.384 8.1 0.32 156 16.7 4.6 0 0.99 0.269 8.1 0.221

117 31.5 13.2 0 0.68 0.38 8.1 0.317 157 17.6 4 0 0.94 0.267 8.1 0.219

118 30 0.13 0 0.77 0.377 8.1 0.314 158 18.1 4.5 0 0.94 0.264 8.1 0.217

119 19.5 14.5 0 0.77 0.373 8.1 0.311 159 20 11.2 0 0.87 0.262 8.1 0.215

120 18.5 14.4 0 0.86 0.37 8.2 0.307 160 23.9 5.17 2.52 0.91 0.26 8.1 0.213


110

161 24 11 1.4 0.91 0.258 8.1 0.211 201 22.48 6.5 0 0.37 0.29 8.5 0.245

162 22.17 7.6 0.53 0.91 0.255 8 0.209 202 22.58 5.2 0 0.43 0.294 8.6 0.248

163 22.08 7.1 0 0.79 0.253 8 0.207 203 22.67 1 0 0.58 0.298 8.6 0.252

164 21.98 8.6 0 0.82 0.251 8 0.205 204 22.77 3.5 0 0.94 0.302 8.6 0.255

165 21.89 6.5 0 0.88 0.249 8 0.203 205 22.87 3.5 0 0.88 0.306 8.6 0.258

166 21.79 5.6 0 0.9 0.246 8 0.202 206 22.96 5.5 0 0.93 0.31 8.7 0.261

167 21.8 4.9 0 0.84 0.247 8 0.202 207 23.06 3.3 0 0.85 0.314 8.7 0.265

168 21.81 8.5 0 0.84 0.248 8 0.203 208 23.16 2.54 0 0.74 0.318 8.7 0.268

169 21.81 13.5 0 0.87 0.249 8 0.204 209 23.25 3.4 0 0.96 0.322 8.7 0.271

170 21.82 11.6 0 0.89 0.25 8.1 0.205 210 23.35 2.4 0 0.8 0.326 8.7 0.275

171 21.83 8.6 0 0.91 0.25 8.1 0.206 211 23.45 4 0 0.76 0.33 8.8 0.278

172 21.84 12.7 0 0.95 0.251 8.1 0.207 212 23.54 4.5 0 0.69 0.333 8.8 0.281

173 21.84 12.5 0 0.94 0.252 8.1 0.208 213 23.64 5.4 0 0.63 0.337 8.8 0.284

174 21.85 9.5 0 0.98 0.253 8.1 0.209 214 23.74 4.6 0 0.59 0.341 8.8 0.288

175 21.85 9.4 0 0.84 0.254 8.1 0.21 215 23.83 5.4 0 0.84 0.345 8.9 0.291

176 21.86 8.1 0 0.93 0.254 8.1 0.211 216 23.93 6 0 0.79 0.349 8.9 0.294

177 21.87 8.3 0 0.94 0.255 8.2 0.211 217 25.4 8.5 0 0.62 0.353 8.9 0.298

178 21.87 4.5 0 0.95 0.256 8.2 0.212 218 22.9 6.01 0 0.79 0.357 8.9 0.301

179 21.88 3.6 0 0.8 0.257 8.2 0.213 219 23.5 6.1 0 0.96 0.361 9 0.304

180 21.89 4.9 0 0.87 0.258 8.2 0.214 220 23.6 6.19 0 0.91 0.365 9 0.307

181 21.89 5.5 0 0.9 0.259 8.2 0.215 221 24 6.27 0 0.81 0.369 9 0.311

182 21.9 4.5 0 0.9 0.259 8.2 0.216 222 24.8 6.36 0 0.59 0.373 9 0.314

183 21.91 4.5 0 0.9 0.26 8.2 0.217 223 27.3 6.45 0 0.5 0.377 9.1 0.317

184 21.92 2.5 0 0.8 0.261 8.3 0.218 224 25.4 6.23 0 0.54 0.381 9.1 0.321

185 21.92 2.8 0 0.82 0.262 8.3 0.219 225 24.4 6.62 0 0.34 0.385 9.1 0.324

186 21.93 5 0 0.95 0.263 8.3 0.219 226 22.2 6.71 0 0.89 0.389 9.1 0.327

187 21.94 3.5 0 0.86 0.263 8.3 0.22 227 21 5.8 0 0.79 0.393 9.1 0.331

188 21.94 3 0 0.86 0.264 8.3 0.221 228 23.5 6.95 0 0.79 0.398 9.1 0.336

189 21.95 4.2 0 0.93 0.265 8.3 0.222 229 25.5 7.11 0 0.82 0.404 9.1 0.341

190 21.95 4 0 0.93 0.266 8.3 0.223 230 26.5 7.27 0 0.61 0.409 9.1 0.347

191 21.96 3.1 0 0.86 0.266 8.3 0.224 231 24.5 7.43 0 0.64 0.415 9.1 0.352

192 21.97 2.5 0 0.68 0.267 8.4 0.225 232 23.5 7.59 0 0.5 0.421 9.1 0.357

193 21.97 5.5 0 0.8 0.268 8.4 0.226 233 24.5 7.74 0 0.75 0.426 9 0.363

194 21.98 9 0 0.88 0.269 8.4 0.227 234 26.3 7.9 0 0.67 0.432 9 0.368

195 21.99 7.3 0 0.94 0.27 8.4 0.228 235 27.5 8.06 0 0.57 0.438 9 0.373

196 22 4.09 0 0.8 0.27 8.4 0.229 236 26.7 8.22 0 0.53 0.443 9 0.379

197 22.09 7.4 0 0.65 0.274 8.4 0.232 237 27.5 8.38 0 0.73 0.449 9 0.384

198 22.19 3.5 0 0.62 0.278 8.5 0.235 238 26.9 8.53 0 0.58 0.455 9 0.389

199 22.29 2.5 0 0.6 0.282 8.5 0.238 239 27.5 8.69 0 0.6 0.46 8.9 0.395

200 22.38 0.1 0 0.66 0.286 8.5 0.242 240 28.8 8.85 0 0.65 0.466 8.9 0.4


111

241 29.8 9.01 0 0.8 0.472 8.9 0.405 281 31 20 0.077 0.43 0.658 8.3 0.575

242 31.8 9.17 0 0.5 0.477 8.9 0.411 282 30.3 19.5 0.08 0.54 0.662 8.3 0.578

243 32.5 9.32 0 0.35 0.483 8.9 0.416 283 36.8 16.5 0.082 0.41 0.666 8.3 0.581

244 33.8 9.48 0 0.33 0.488 8.9 0.422 284 28.1 18 0.084 0.27 0.67 8.3 0.585

245 33.5 9.64 0 0.28 0.494 8.8 0.427 285 23.7 14.6 0.086 0.65 0.674 8.3 0.588

246 34.5 9.8 0 0.53 0.5 8.8 0.432 286 30 11.6 0.089 0.75 0.678 8.3 0.592

247 33.4 9.96 0 0.45 0.505 8.8 0.438 287 32.5 13 0.091 0.77 0.682 8.3 0.595

248 24.5 10.11 0 0.35 0.511 8.8 0.443 288 34 13.6 0.093 0.5 0.685 8.2 0.598

249 31.4 10.3 0 0.72 0.517 8.8 0.448 289 34.2 12.5 0.097 0.31 0.685 8.2 0.597

250 32.64 10.43 0 0.8 0.522 8.8 0.454 290 35.7 15.1 0.102 0.4 0.684 8.2 0.596

251 25.5 10.59 0 0.31 0.528 8.7 0.459 291 34.6 15.4 0.106 0.44 0.683 8.2 0.595

252 29.2 10.75 0 0.67 0.534 8.7 0.464 292 36.5 19.5 0.11 0.36 0.682 8.2 0.594

253 35.2 10.9 0 0.6 0.539 8.7 0.47 293 30.5 20 0.115 0.44 0.681 8.2 0.593

254 28.5 11.06 0 0.5 0.545 8.7 0.475 294 32 16.5 0.119 0.61 0.68 8.1 0.592

255 22.2 11.2 0 0.3 0.551 8.7 0.48 295 27.2 17.3 0.123 0.62 0.679 8.1 0.59

256 33.5 11.38 0 0.7 0.556 8.6 0.486 296 29.9 14 0.127 0.73 0.678 8.1 0.589

257 35.6 11.54 0 0.9 0.562 8.6 0.491 297 31.6 16.5 0.132 0.65 0.677 8.1 0.588

258 24.6 11.69 0 0.4 0.568 8.6 0.497 298 34.5 17.9 0.136 0.56 0.676 8.1 0.587

259 22.5 11.83 0 0.6 0.571 8.6 0.5 299 25.5 17.5 0.14 0.55 0.675 8 0.586

260 29.5 11.97 0 0.7 0.575 8.6 0.503 300 20.5 16 0.145 0.93 0.674 8 0.585

261 27.2 12.1 0 0.8 0.579 8.6 0.507 301 23.9 14.5 0.149 0.95 0.673 8 0.583

262 23.2 12.24 0 0.6 0.583 8.6 0.51 302 28.2 13 0.153 0.95 0.672 8 0.582

263 20 12.38 0 0.7 0.587 8.6 0.513 303 31.6 14.9 0.157 0.69 0.671 8 0.581

264 24.2 12.51 0 0.8 0.591 8.5 0.517 304 26.29 15.4 0.162 0.62 0.67 8 0.58

265 24.9 12.65 0 0.8 0.595 8.5 0.52 305 25 15 0.166 0.94 0.669 7.9 0.579

266 25.7 12.79 0 0.71 0.599 8.5 0.524 306 30.3 14 0.17 0.84 0.668 7.9 0.578

267 27.3 12.93 0 0.72 0.603 8.5 0.527 307 32.2 16.5 0.175 0.88 0.667 7.9 0.576

268 33 13.06 0 0.75 0.607 8.5 0.531 308 34.6 14 0.179 0.6 0.666 7.9 0.575

269 34.7 13.2 0 0.47 0.611 8.5 0.534 309 35 17 0.183 0.72 0.665 7.9 0.574

270 27.5 13.34 0 0.38 0.615 8.5 0.537 310 31.5 20.4 0.188 0.32 0.664 7.9 0.573

271 32 13 0 0.61 0.619 8.5 0.541 311 31 18.5 0.192 0.61 0.663 7.8 0.572

272 34.4 13.7 0 0.68 0.623 8.4 0.544 312 32.6 16.5 0.196 0.61 0.662 7.8 0.571

273 33.5 15.5 0 0.53 0.626 8.4 0.547 313 35.7 16.2 0.2 0.53 0.661 7.8 0.569

274 35.5 14.1 0 0.43 0.63 8.4 0.551 314 35 20 0.205 0.44 0.66 7.8 0.568

275 32 18 0 0.33 0.634 8.4 0.554 315 36 17 0.209 0.48 0.659 7.8 0.567

276 29.5 15 0 0.36 0.638 8.4 0.558 316 34.3 15.8 0.213 0.51 0.658 7.7 0.566

277 30.4 12.7 0 0.63 0.642 8.4 0.561 317 33.2 18 0.218 0.67 0.657 7.7 0.565

278 35.1 16 0 0.76 0.646 8.4 0.564 318 31.4 14 0.222 0.3 0.656 7.7 0.564

279 36 16.5 0 0.4 0.65 8.4 0.568 319 32.1 14 0.226 0.5 0.65 7.7 0.563

280 36.2 19.4 0.075 0.37 0.654 8.3 0.571 320 30.7 19.5 0.228 0.7 0.654 7.7 0.561


112

321 31.9 19.1 0.23 0.6 0.652 7.6 0.56

322 29.5 18.04 0.232 0.6 0.651 7.6 0.558

323 24 17.4 0.233 0.7 0.65 7.6 0.557

324 28.5 11 0.235 0.5 0.648 7.5 0.556

325 28 18.16 0.24 0.6 0.647 7.5 0.554

326 26.2 18 0.239 0.64 0.645 7.5 0.553

327 28.5 20 0.241 0.71 0.643 7.4 0.552

328 34.4 14.11 0.242 0.61 0.642 7.4 0.55

329 33 15 0 0.54 0.641 7.3 0.549

330 32.5 20.4 0 0.64 0.639 7.3 0.547

331 26.5 18.5 0 0.67 0.638 7.3 0.546

332 32.1 20 0 0.73 0.636 7.2 0.545

333 31 20.5 0 0.8 0.634 7.2 0.543

334 29.5 18.5 0 0.7 0.633 7.2 0.542

335 26.2 18.5 0 0.79 0.632 7.1 0.541

336 31.2 17.4 0 0.67 0.63 7.1 0.539

337 33.9 15 0 0.46 0.629 7.1 0.538

338 33.8 16 0 0.41 0.627 7 0.537

339 32 17 0 0.59 0.625 7 0.535

340 34.5 18.5 0 0.49 0.624 7 0.534

341 35 19 0 0.48 0.623 6.9 0.532

342 37.3 20 0 0.51 0.621 6.9 0.531

343 26.5 21 0 0.79 0.62 6.9 0.53

344 29.1 23 0 0.8 0.618 6.8 0.528

345 28.9 20.43 0 0.83 0.616 6.8 0.527

346 32.5 20.15 0 0.68 0.615 6.8 0.526

347 24.5 18.6 0 0.76 0.614 6.7 0.524

348 31.4 19 0 0.63 0.612 6.7 0.523

349 31.5 14 3 0.46 0.611 6.7 0.522

350 32.5 16.7 3.2 0.57 0.612 6.7 0.523

351 33.4 15.5 0.2 0.47 0.614 6.8 0.524

352 34.5 16.54 0.3 0.49 0.615 6.8 0.525

353 34 18 0 0.68 0.617 6.9 0.527

354 33 19.5 0 0.54 0.618 6.9 0.528

355 29.6 20.5 0 0.82 0.62 6.9 0.529

356 28 19 0 0.91 0.621 7 0.53

357 31 18 0 0.53 0.76 7 0.532

358 34 17.5 0 0.58 0.624 7.1 0.533

359 32.6 18 0 0.59 0.626 7.1 0.534

360 29 20.5 0 0.66 0.628 7.2 0.535

361 27.3 18.5 0 0.74 0.629 7.2 0.537

362 33.8 19 0.62 0.63 0.631 7.3 0.538

363 37 16 0 0.37 0.632 7.3 0.539

364 34.1 18.5 0 0.57 0.634 7.4 0.54

365 33.3 21 0 0.73 0.635 7.4 0.542


113

Appendix D (a): Generic data values for maize and sorghum

Maize Sorghum Photosynthetic mechanism C4 C4 Threshold temperature TO TSUM

10 1600

10 1600

Rooting zone RDS Rooting depth initial Maximum

10 100-170

5-10 100-200

Critical leaf water heads PSI leaf

17000

20000

SLA range 14-35 11-21 Extinction coefficient visible light ke 0.6 0.5 Maintenance respiration r(org) Root Leaf Stem S.O

0.010 0.013 0.010 0.010

0.010 0.015 0.010 0.010

Heat sum for development tissue EC (org) Leaf Root Stem s.o

0.72 0.72 0.69 0.72

0.72 0.72 0.69 0.74

Appendix D(b): Generic data values

Maize Sorghum RDS 0 0.2 0.3 0 0.22 0.34 0.56 0.61 Fr (leaf) 0.60 0.70 0.65 0.45 0.55 0.65 0.25 0.13 Fr (root) 0.40 0.30 0.23 0.55 0.33 0.25 0.05 0.00 Fr (stem) 0.00 0.00 0.12 0.00 0.01 0.10 0.70 0.80 Fr (s.o) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07


114

Appendix E: Growth cycle for maize and sorghum

Establishment Vegetative Flowering Yield Ripening Maize 15-25 25-40 15-20 35-45 10-15 Sorghum 15-20 20-30 15-20 35-40 10-15 Source:(Doorenbos and Kassam, 1979)

Appendix F: Glossary

ASSC is Actual surface storage SSC is equivalent to surface storage capacity (cm) (CR+D) is the net rate of water flow through the lower boundary of the rooting zone (cm d-1) Dr is surface roughness or furrow depth (cm) SIG is clod angle or furrow angle (degree) PHI is average slope of the land (degree) SLA is specific leaf area, m2 kg -1 TO is threshold temperature for development, oC Tsum is heat requirement for full development, oC d Ke is the extinction coefficient for visible light K is the hydraulic conductivity LAI is leaf area index LC is land characteristic LUR is land use requirement PSIint is the matric suction at planting or germination (cm) (ψ) RD is equivalent depth of the rooting zone (cm) RDSroot is reletive development stage. RSM is the rate of change of volume fraction of moisture in the rooting zone (cm) SSC is equivalent surface storage capacity Tleaf is heat sum for full development of leaf tissue TR is the actual rate of transpiration (cm d-1) UPFLUX is the net of water vapour flow through the upper boundary of the rooting zone (cm d-1) ZTint is depth of phreatic level at planting Ψ is matric suction


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Appendix G: Questionnaire Farmer 1 Location: 460594, 7520848 Farm size: 5.3ha Type of crops grown: maize Land tenure: customary Farm operations: Ploughing and planting are done at the same time in Nov /Dec Weeding is done only once Fertilizer application: No fertilizer is used Harvesting: in May when the crop is completely dry Input acquisition: buys cash Power: uses animal draught (donkeys) Labour supply: Family labour Labour intensity: intensity is high during weeding and harvesting time Yield: could not disclose the yield Cropping system: single cropping Fallowing: no fallowing Performance of the farm: no variations in the performance Problems faced: corn crickets Control: by hand picking Extension services: access to agriculture extension services Note: is a model farmer Farmer 2 Location: 463636, 7519154 Farm size: 7ha but uses only 3ha; the remainder is used for grazing livestock Type of crops grown: maize and sorghum Land tenure: customary Farm operations: land preparation and planting done at the same time when rains come in November Weeding is done after two months Fertilizer application: Does not apply fertilizers Harvesting; May/June Input acquisition: Cash Power: animal draught (donkeys) Labour supply: family members Labour intensity: medium intensity Yield: 7bags of 70kgs maize and 15bags of 70kg for sorghum Cropping system: Mixed cropping Fallowing: Does not fallow Performance of the farm: part of the farm is stony and performance is poor in that area Problems faced: High winds sooner after emergency of the seedlings and sorghum Birds attacking sorghum Sealing of the soil


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Solution: there is no control for wind, as for birds, they are scared and nothing done for the sealing problem Extension services: Has access to agricultural extension services Farmer 3 Location: 464878, 7519907 Type of crops grown: sorghum, maize, cowpeas, and pumpkins Land tenure: customary Farm operations: land preparation and planting are done simultaneously Weeding is done in December Fertilizer application: no fertilizer application Harvesting: My/June Input acquisition: Recycled seed Power: Animal draught Labour supply: Family labour for weeding Labour intensity: high labour intensity Yield: 10bags of 70kg maize, 15bags of 70kg sorghum Cropping system: single cropping Fallowing: No fallowing Performance of the farm: Eroded area gives low yield Problems faced: Soil erosion, sealing, birds and aphids on cowpeas Solution: makes box ridges for soil erosion scaring away birds but no solution for the rest of the problems Extension services: gets access to agricultural services Farmer 4 Location: 481118, 7537905 Farm size: 5.5ha Type of crops grown: sorghum, maize and cowpeas Land tenure: customary Farm operations: land preparation and planting at the same time in Nov/Dec Weeding is done once Fertilizer application; no fertilizer applied Harvesting: June Input acquisition: Cash (50kg in total for all crops) Power: animal draught (donkeys) Labour supply: Family members for weeding Labour intensity: High Yield: 13 bags of 70kg sorghum, 8 bags of 70kg Cropping system: single cropping Fallowing: no fallowing Performance of the farm: no variations Problems faced: wind erosion, aphids on sorghum, sealing Solution: no solution provided


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Extension services: have access to agricultural services Farmer 5 Location: 485189, 7539910 Farm size: 10ha Type of crops grown: sorghum, maize and cowpeas Land tenure: customary Farm operations: land preparation and planting at the same time Weeding is done in December Fertilizer application Harvesting Input acquisition: Uses recycled seed but sometimes buys cash Power: Donkeys Labour supply: Family members Labour intensity: high intensity during weeding Yield: 41bags of 70kg maize Cropping system: Mixed cropping Fallowing: At times 5ha may be fallowed for only one year Performance of the farm: Experience low yield on sloping side Problems faced: water and wind erosion Solution: planted trees to act as wind break but died due to lack of moisture Extension services: Get access to agricultural extension services Farmer 6 Location: 484385, 7538250 Farm size: 3ha Type of crops grown: sorghum Land tenure: customary Farm operations: Ploughing and planting simultaneously Weeding done once when weeds appear Fertilizer application: no fertilizer application Harvesting: done in May when the crop is dry Input acquisition: Uses recycled seed Power: Uses donkeys Labour supply: Family members Labour intensity: Medium intensity Yield: 70 bags of 70kg each Cropping system: Single cropping Fallowing: No fallowing Performance of the farm: No variations in the performance of the farm Problems faced: Birds Solution: No control Extension services: Get access to agricultural extension services Farmer 7 Location: 484223, 7538215


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Farm size: 6ha Type of crops grown: sorghum, maize and cowpeas Land tenure: customary Farm operations: Ploughing and planting done simultaneously in November Weeding is done once Fertilizer application: No fertilizer is applied Harvesting: Done in May/June Input acquisition: Uses recycled seed but sometimes buys using cash Power: Uses donkeys Labour supply: Family members but sometimes employ casual labour for weeding Labour charge: Pays P5 per person per day depending on availability of finances Labour intensity: Medium intensity Yield: could not disclose Cropping system: single cropping Fallowing: no fallowing Performance of the farm: Part of the farm has sandy soils and get low yield on that side Problems faced: birds attacking sorghum Solution: by scaring the birds away Extension services: get access to agricultural extension services Farmer 8 Location: 463159, 7517322 Farm size: 19.5ha but uses only 5ha Type of crops grown: sorghum and maize Land tenure: customary Farm operations: Ploughing and planting done simultaneously Weeding: done when weeds appear Fertilizer application: does not apply fertilizer Harvesting: In May/June Input acquisition: cash Power: draught animals (donkeys) Labour supply: Family members but sometimes employ casual labour for weeding Labour intensity: medium intensity Labour charge: P15 per person per day and can employ a maximum of 5 Yield: 11bags of 70kg for sorghum and 17bgas of 70kg for maize Cropping system: single cropping Fallowing: Fallow for one year Performance of the farm: There are some pans in the field where yield is lower than the rest Problems faced: stalkborers and sealing but is not serious Solution: No control measure Extension services: Has access to Agricultural extension services


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Farmer 9 Location: 463153, 7517319 Farm size: 10ha but uses only 7ha Type of crops grown: sorghum and maize Land tenure: Customary Farm operations: Ploughing and planting done simultaneously Weeding: done when weeds appear and weeds only once Fertilizer application: does not apply fertilizer Harvesting: in June Input acquisition: Uses recycled and plants 8kg ha-1 for sorghum and 10kg ha-1 Power: Draught animals Labour supply: prepares traditional beer to people working on the farm Labour intensity: high labour intensity Yield: 1bag of 70kg for each crop Cropping system: single cropping Fallowing: does fallow for one season Performance of the farm: part of the farm has cynodon dactylon and competes with crop leading to low yield Soil and water conservation: does not practise any Problems faced: soil erosion, birds and elegant grasshoppers Scaring them away controls birds, elegant grasshoppers are hand picked and no measure control for erosion Extension services: Has access to agricultural extension services Farmer 10 Location: 466658, 7510188 Farm size: 7ha Type of crops grown: sorghum, maize and cowpeas Land tenure: Customary Farm operations Ploughing and planting done simultaneously Weeding: done when weeds appear and weeds only once Fertilizer application: does not apply fertilizer Harvesting: in June Input acquisition: buys cash: 10P per 10kg Power: animal draught Labour supply: family members Labour intensity: medium Yield: 30bags of 70kg for maize and no yield for sorghum due to bird’s attack Cropping system: single cropping Fallowing: no fallowing Performance of the farm: no variations in performance Problems faced: Cynodon dactylon weed, birds and elegant grasshoppers Solution: no control Extension services: Has access to agricultural extension services


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Farmer 11 Location: 466643, 7510139 Farm size: 8ha Type of crops grown: maize, sorghum and cowpeas Land tenure: Farm operations Ploughing and planting done simultaneously Weeding: done when weeds appear and weeds only once Fertilizer application: does not apply fertilizer Harvesting: in June Input acquisition: cash Power: animal draught Labour supply: family members for weeding Labour intensity: Low Yield: 5gags of 70kg for each crop Cropping system: single cropping Fallowing: no fallowing Performance of the farm: no variations Problems faced: the farmland is stony, birds attacking sorghum Solution: scaring the birds away Extension services: has access to agricultural extension services Farmer 12 Location: 467185, 7518324 Farm size: 8ha Type of crops grown: sorghum and maize Land tenure: Customary Farm operations Ploughing and planting done simultaneously Weeding: done when weeds appear and weeds only once Fertilizer application: does not apply fertilizer Harvesting: in June Input acquisition: cash, buys 3-4 bags of 10kg at 3P/kg Power: Animal draught Labour supply: Family labour for weeding Labour intensity: medium Yield: 7bags of 70kg of sorghum and 3bags of 70kg of maize Cropping system: single cropping Fallowing: fallow for one season Performance of the farm: no variations in performance Problems faced: soil erosion, birds attacking sorghum corn cricket attacking maize Solution: scaring the birds away and no control for corn crickets Extension services: Does not have access to agricultural services


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Appendix H: Results of Particle size distribution analysis

Code X_coord Y_coord Sand (%) Silt (%) Clay (%) Texture

SPT_002 428575 7531451 95.324 1.306 3.370 Sand

SPT_002 428575 7531451 94.094 1.115 4.791 SandSPT_002 428575 7531451 92.929 0.534 6.537 SandHARD_13 466995 7514049 93.998 1.414 4.589 SandHARD_13 466995 7514049 92.268 1.693 6.039 Sand

HARD_13 466995 7514049 91.757 1.563 6.680 SandHPT_001 466980 7513874 91.719 4.983 3.297 SandHPT_001 466980 7513874 91.983 1.897 6.120 SandHPT_001 466980 7513874 89.443 1.610 8.947 Loamy sand

HPT_003 465347 7507938 91.719 4.983 3.297 SandHPT_003 465347 7507938 91.983 1.897 6.120 SandHPT_003 465347 7507938 89.443 1.610 8.947 Loamy sandSPT_003 444677 7516908 94.395 0.872 4.733 Sand

SPT_003 444677 7516908 94.704 0.659 4.637 SandSPT_003 444677 7516908 92.371 1.314 6.315 SandEPT_002 475066 7535877 87.671 4.110 8.219 Loamy sandEPT_002 475066 7535877 87.240 3.683 9.078 Loamy sand

HPT_007 467604 7519059 71.099 15.973 12.928 Sandy LoamHPT_007 467604 7519059 60.365 19.681 19.954 Sandy LoamHPT_007 467604 7519059 73.317 15.570 11.114 Sandy LoamHPT_005 469774 7518089 23.544 31.646 44.810 ClayHPT_005 469774 7518089 22.993 25.571 51.436 Clay

HPT_005 469774 7518089 24.561 26.816 48.623 ClayHPT_005 469774 7518089 18.324 30.823 50.853 ClayHPT_06 467215 7517154 56.178 15.084 28.737 Sandy clay loamHPT_06 467215 7517154 19.969 38.555 41.476 Clay

HPT_06 467215 7517154 68.239 6.646 25.115 Sandy clay loamEPT_01 474663 7539777 88.573 3.809 7.618 Loamy sandEPT_01 474663 7539777 88.316 3.372 8.311 Loamy sandSPT_1 433495 7527033 77.185 12.609 10.206 Sandy Loam

ESC_10 479088 7539915 78.447 12.576 8.977 Sandy LoamESC_07 470500 7537503 58.666 17.109 24.225 Sandy clay loamESC_11 470089 7534546 58.561 13.760 27.679 Sandy clay loamESC_30 473503 7517178 46.700 18.946 34.354 Sandy clay loam

ESC_14 471662 7532578 56.033 16.592 27.375 Sandy clay loamSand_17 425914 7534098 96.904 0.888 2.208 SandSand_ 43 431077 7530673 96.953 0.932 2.115 SandSand_ 56 433493 7527033 94.695 1.364 3.941 SandHard_01 460013 7510014 94.138 1.036 4.826 Sand

Hard_32 466630 7513081 91.884 2.977 5.139 SandHard_11 461741 7511696 26.555 71.998 1.447 Silt loamHard_54 469767 7518092 22.824 29.453 47.723 ClayHard_56 467597 7519066 64.894 16.929 18.177 Sandy loam

Esc_58 474799 7535997 93.815 2.930 3.255 SandFarm_01 460594 7520848 87.109 2.902 9.989 Loamy sandFarm_02 463636 7519154 86.356 2.886 10.758 Loamy sandFarm_03 464878 7519907 77.430 5.061 17.509 Sandy Loam


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Appendix I: Decision trees LUT1 Erosion hazard > Slp (Slope) <3 (none) [0-3 %]....... : 1 (none) 3-8 (slight) [3-8 %] > Txc (Textural class) FS (Fine sand) [3-10 cla : 2 (slight) SL (Sandy loam) [10-15 c : =1 LS (Loamy sand) [15-20 c : =1 CL (Clay loam) [20-50 cl : 1 (none) SCL (Sandy clay loam) [5 : =4 9-16 (moderate) [8-16 %] : 3 (moderate) >16 (severe) [16-25 %].. : 4 (severe) LUT1,Oxygen availability > Drg (Soil drainage class) Wd (Well drained)....... : 1 Mod (Moderately drained) : 2 Imp (Imperfectly drained : 3 Pr (Poorly drained)..... : 4 LUT1,Moisture availability > TRf (Total rainfall) 250-300 (not adequate) [ : 4 (severe stress) 300-400 (Stress) [300-400 mm] > SEDth (Soil effective depth) <30 (very shallow) [0-30 : 4 (severe stress) 30-50 ( shallow) [30-50 cm] > Txc (Textural class) FS (Fine sand) [3-10 class] > Yd (LUT1 Yield class) ns (not suitable) [1500-] : 4 (severe stress) ms (marginally suitable) : 3 (stress) mod.s (moderately suitab) : =2 suit (suitable) [6000-65] : 2 (slightly adequat) SL (Sandy loam) [10-15 c : =1 LS (Loamy sand) [15-20 c : =1 CL (Clay loam) [20-50 cl : 2 (slightly adequat) SCL (Sandy clay loam) [5 : =4 50-120 (slightly deep) [ : 3 (stress) 500 (deep) [120-500 cm]. : 2 (slightly adequat) 400-600 (Less adequate) [400-600 mm] > SEDth (Soil effective depth) <30 (very shallow) [0-30 : 3 (stress) 30-50 ( shallow) [30-50 : 2 (slightly adequat) 50-120 (slightly deep) [ : 1 (adequate) 500 (deep) [120-500 cm]. : =3 >600 (Adequate) [600-750 mm]>SEDth(Soil effective depth) <30 (very shallow) [0-30 : 2 (slightly adequat) 30-50 ( shallow) [30-50 : 1 (adequate) 50-120 (slightly deep) [ : =2 500 (deep) [120-500 cm]. : =2


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LUT1,Rooting Condition > SEDth (Soil effective depth) <30 (very shallow) [0-30 : 4 (poor) 30-50 ( shallow) [30-50 cm] > Drg (Soil drainage class) Wd (Well drained)....... : 1 (very good) Mod (Moderately drained) : 2 (good) Imp (Imperfectly drained : 3 (moderate) Pr (Poorly drained)..... : 4 (poor) 50-120 (slightly deep) [ : 2 (good) 500 (deep) [120-500 cm]. : 1 (very good LUT1,Soil workability > Txc (Textural class) FS (Fine sand) [3-10 cla : 1 SL (Sandy loam) [10-15 c : =1 LS (Loamy sand) [15-20 c : 2 CL (Clay loam) [20-50 cl : =3 SCL (Sandy clay loam) [5 : =4 LUT 2,Erosion hazard > Slp (Slope) <3 (none) [0-3 %]....... : 1 (none) 3-8 (slight) [3-8 %] > Txc (Textural class) FS (Fine sand) [3-10 c : 2 (slight) SL (Sandy loam) [10-15 c : 3 (moderate) LS (Loamy sand) [15-20 c : =2 CL (Clay loam) [20-50 c : =3 (moderate) SCL (Sandy clay loam) [5 : 2 (slight) 9-16 (moderate) [8-16 %] : 3 (moderate) >16 (severe) [16-25 %].. : 4 (severe) LUT 2,Rooting condition > SEDth (Soil effective depth) <30 (very shallow) [0-30 : 4 (poor) 30-50 ( shallow) [30-50 cm] > Txc (Textural class) FS (Fine sand) [3-10 cla : 1 (very good) SL (Sandy loam) [10-15 c : =1 LS (Loamy sand) [15-20 c : 2 (good) CL (Clay loam) [20-50 cl : =3 SCL (Sandy clay loam) [5 : =4 50-120 (slightly deep) [ : 2 (good) 500 (deep) [120-500 cm]. : 1 (very good)


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LUT 2,Sealing > Txc (Textural class) FS (Fine sand) [3-10 cla : 1 (no problem) SL (Sandy loam) [10-15 c : =1 LS (Loamy sand) [15-20 c : 2 (slight prob) CL (Clay loam) [20-50 cl : 2 (slight prob) SCL (Sandy clay loam) [5 : LUT 2,Soil workability > Txc (Textural class) FS (Fine sand) [3-10 cla : 1 (Easy) SL (Sandy loam) [10-15 c : =1 LS (Loamy sand) [15-20 c : 2 (Moderate) CL (Clay loam) [20-50 cl : =3 SCL (Sandy clay loam) [5 : =4 LUT 2,Oxygen availability > Drg (Soil drainage class) Wd (Well drained)....... : 1 (no limitation) Mod (Moderately drained) : 2 (slight limit) Imp (Imperfectly drained : 4 (poor) Pr (Poorly drained)..... : =3 LUT 2,Moisture availability > TRf (Total rainfall) 250-300 (not adequate) [ : 4 (severe stress) 300-400 (Stress) [300-400 mm] > Txc (Textural class) FS (Fine sand) [3-10 cla : 4 (severe stress) SL (Sandy loam) [10-15 class] > Yd LUT2 (LUT2 yield class) ns (not suitable) [0-1000] : 3 (stress) ms (marginally suitable) : 3 (stress) mod.s (moderately suitab : 2 (less adequate) suit (suitable) [2000-3000] : 1 (adequate) LS (Loamy sand) [15-20 c : 3 (stress) CL (Clay loam) [20-50 cl : =3 SCL (Sandy clay loam) [5 : 2 (less adequate) 400-600 (Less adequate) : 1 (adequate) >600 (Adequate) [600-750 : =3

EVALUATING THE IMPORTANCE OF SOIL MOISTURE … · 1.1 importance of agriculture in the southern...

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